เงื่อนไขการค้นหา

ทักษะ:

Compliance, Production Engineering, Python

ประเภทงาน:

งานประจำ

• As an AI Engineer Lead, you will lead the end-to-end engineering delivery of AI products from concept and prototype to production deployment and continuous improvement. The role combines hands-on technical leadership, solution architecture, AI/ML engineering, and cross-functional delivery to ensure AI solutions are reliable, reusable, secure, and measurable in business value.
• Lead AI Solution Delivery Lead the design, development, deployment, and continuous improvement of AI solutions, including machine learning models, LLM-powered applicati ...
• Provide Technical Leadership Lead and coach data scientists, machine learning engineers, and AI engineers on solution design, coding standards, model development, and production engineering practices. Provide hands-on technical direction to ensure AI solutions are robust, maintainable, reusable, and aligned with enterprise technology and security standards..
• Build Production-Ready AI Platforms and Applications Architect and implement AI/ML computing environments, application stacks, APIs, batch pipelines, real-time inference services, model monitoring, and production support mechanisms. Apply engineering best practices such as Python development, MLOps, CI/CD, automated testing, documentation, deployment automation, and release management..
• Apply now if you have these advantages.
• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Technology, or a related field.
• 7+ years of experience in software engineering, data science, machine learning engineering, or AI solution delivery, with proven experience leading complex AI implementation projects or technical teams.
• Strong hands-on experience in machine learning, deep learning, generative AI, LLM-based application development, retrieval-augmented generation, and agentic AI solution patterns.
• Proficiency in Python and practical experience with AI/ML libraries, orchestration frameworks, API development, data pipelines, model serving, and monitoring.
• Strong understanding of MLOps, DevOps, CI/CD, model lifecycle management, testing, deployment automation, and production support practices.
• Strong leadership, communication, analytical, and problem-solving skills, with the ability to manage priorities and drive outcomes across technical and business stakeholders.
• Cloud, AI/ML, data engineering, or software engineering certifications such as AWS Certified Machine Learning, or related credentials.
• Experience delivering AI solutions in regulated industries such as banking, insurance, or financial services.
• Experience with enterprise AI platforms, vector databases, AI agent orchestration, and LLM evaluation frameworks.
• Why join Krungsri?.
• As a part of MUFG (Mitsubishi UFJ Financial Group), we a truly a global bank with networks all over the world.
• We offer a striking work-life balance culture with hybrid work policies (3 days in office per week).
• Unbelievable benefits such as attractive bonuses, employee loan with special rates and many more.
• Apply now before this role is close. **.
• FB: Krungsri Career(http://bit.ly/FacebookKrungsriCareer [link removed]).
• LINE: Krungsri Career (http://bit.ly/LineKrungsriCareer [link removed]).
• Talent Acquisition Department.
• Bank of Ayudhya Public Company Limited.
• 1222 Rama III Rd., Bangpongpang, Yannawa, Bangkok 10120.
• สอบถามข้อมูลเพิ่มเติม: Talent Acquisition Center 0-2-----000.
• หมายเหตุ ธนาคารมีความจำเป็นและจะมีขั้นตอนการตรวจสอบข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของผู้สมัคร ก่อนที่ผู้สมัครจะได้รับการพิจารณาเข้าร่วมงานกับธนาคารกรุงศรีฯ.
• Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank.
• Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
• EN (https://krungsri.com/b/privacynoticeen).
• ผู้สมัครสามารถอ่านประกาศการคุ้มครองข้อมูลส่วนบุคคลส่วนงานทรัพยากรบุคคลของธนาคารได้โดยการพิมพ์ลิงค์จากรูปภาพที่ปรากฎด้านล่าง.
• ภาษาไทย (https://krungsri.com/b/privacynoticeth).

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Leadership Skill, Big Data, Python, English

ประเภทงาน:

งานประจำ

• Architect and optimize high-throughput data pipelines and unstructured data processing frameworks to directly power the enterprise AI Foundation Platform.
• Co-own the vector infrastructure alongside the AI Engineer Specialist, ensuring optimized embedding storage, indexing strategies, and fast vector search retrieval.
• Build automated ETL/ELT pipelines capable of transforming raw enterprise data into AI-ready formats (chunking, metadata tagging, and cleaning).
• Data Governance, Metadata & Cataloging.
• Implement metadata pipelines for comprehensive data catalog and data dictionary services, including schema capture, lineage tracking, and audit logging.
• Enforce data governance, access controls, and privacy compliance across all data stores used for training, fine-tuning, and RAG retrieval.
• Design and maintain operational data lineage to ensure transparency and auditability of data flowing into production AI models.
• Advanced AI Component Integration.
• Develop and tune robust data ingestion pipelines for OCR, NLP processing, recommendation systems, and multi-modal AI inputs.
• Optimize data tiering and caching strategies to reduce latency and infrastructure costs for live enterprise AI workloads.
• Build secure, scalable data connectors linking legacy enterprise databases with modern LLM frameworks and autonomous agents.
• Collaboration & Data Excellence.
• Partner directly with the AI Engineer Specialist to ensure seamless data delivery for real-world, high-concurrency production deployments.
• Bridge traditional data engineering practices with modern MLOps, setting up automated data validation, quality checking, and drift detection at the data layer.
• Provide data-level expertise during architecture reviews, ensuring scalable data design patterns across the entire AI project lifecycle.
• Key Impacts.
• Ensure high-quality, AI-ready data ingestion at scale, dramatically reducing the time-to-market for enterprise AI assets.
• Establish a secure and compliant data foundation that guarantees enterprise data privacy during AI model interactions.
• Eliminate data bottlenecks in real-world production environments, ensuring sub-second latency for enterprise RAG and search systems.
• Transition traditional data warehouses and lakes into future-ready, graph- and vector-enabled AI data infrastructure.
• Master's or Bachelor's degree in Computer Engineering, Computer Science, Data Engineering, or a related technical field.
• 5+ years of experience in heavy-duty Data Engineering, Big Data, or Distributed Systems, with strong production experience in an AI/ML context.
• Proven track record of building large-scale data infrastructure supporting live, mission-critical applications.
• Technical & AI Data Framework Expertise.
• Deep experience in Python and SQL, alongside modern big data tools (e.g., Spark, Kafka, or cloud equivalents).
• Hands-on expertise in Vector Databases and unstructured data processing.
• Strong understanding of data chunking strategies, text extraction (OCR/NLP pipelines), and metadata orchestration.
• Familiarity with cloud data platforms (AWS/Azure/GCP) including managed data lakes, data warehouses, and cloud-native security/encryption.
• Real-world experience implementing data catalogs, schema evolution, and automated data quality monitoring.
• Leadership & Soft Skills.
• Excellent technical communication skills to align data pipeline designs with AI model engineering requirements.
• Strong analytical and problem-solving mindset, comfortable handling noisy, unstructured enterprise data under tight deadlines.
• Good verbal and written English communication skills for vendor engagement and cross-functional team collaboration.

ทักษะ:

Software Development, Recruitment, Assurance, Python, Docker, C++

ประเภทงาน:

ฝึกงาน

• Located in the heart of Bangkok's Phrom Phong District, Sertis is ASEAN's leading Data and AI engineering and solutions company. Since 2014, our advanced solutions and products have powered over 400 enterprise Data and AI deployments at the region's leading companies and conglomerates.
• We are also a member firm of Andersen Consulting, a global consulting practice integrating business strategy, digital transformation, and AI-driven technology solutions with Andersen Global's world-class expertise.
• What We Do.
• Sertis provides both productized and bespoke AI and Data solutions for our Customers, optimizing and commercializing their data in ways that activate real business results. Our 140+ team have developed product offerings and IP ranging from advanced Computer Vision applications accredited Global Top 20 by NIST, to automated insights monetization for Retailers, eKYC for financial institutions, AI-driven agricultural safety assurance, precision steel cutting, trading algorithms for hedge funds, and enterprise knowledge management systems based on AI.
• Our Aspiration.
• We are data and AI pioneers, dedicated to enhancing the economic and social lives of our customers via technology. We are not just living in history, we are making history everyday. In becoming one of the world's leading Data and AI companies, we always double-down on remaining a place where a diverse mix of talent wants to come, do their best work, and stay. We pride ourselves on bringing the best talent worldwide into a culture that encourages learning, growth opportunities, innovative contributions, and a sense of ownership.
• As part of Andersen Consulting, we are committed to delivering best-in-class Data and AI solutions aligned with a global platform known for innovation, integration, and impact while continuing to set benchmarks in the region and beyond.
• sertiscorp.com.
• This role is for candidates who are available to work as interns during.
• Winter Internship 2026.
• Who is Sertis?.
• Sertis is a leading Data and AI company based in the heart of Bangkok. We provide both off-the-shelf and customized solutions for our clients ranging from data infrastructure, BI development, and data-driven business insights to forecasting, optimization, and computer vision. Our expert team of data and AI consultants work closely with clients, across different industries such as retail, manufacturing, banking, energy, airlines, agriculture, and healthcare, to understand their business needs and deliver bespoke solutions using cutting-edge technologies that are just right for them.
• Our aim is to be one of the leading Data and AI companies globally, where a diverse mix of talent want to come, stay, and do their best work. We pride ourselves on bringing not only the best, but also nice, talent from around the World. We recognise that our company runs on our people's hard work and dedication while maintaining a culture that encourages learning, growth opportunity, innovative contribution, and a sense of ownership.
• https://www.sertiscorp.com/.
• As a.
• Machine Learning Engineer Intern at Sertis,.
• you will gain hands-on experience supporting the productionization of data science research and AI-driven solutions. You will work alongside experienced ML engineers to understand how AI models are deployed on diverse hardware platforms, assist in building MLOps infrastructure, and contribute to writing production-grade software for model inference. This internship is an excellent opportunity to apply your academic knowledge to real-world generative AI projects and agentic systems within a fast-paced, collaborative environment.
• Support cross-functional teams in understanding business requirements and contribute to designing ML solutions to address those needs.
• Assist in.
• developing and maintaining scalable infrastructure for model training and deployment.
• under the guidance of senior engineers.
• Help.
• develop cloud-native APIs, pipelines,.
• and general software components for model inference.
• Gain exposure to cutting-edge foundation models and assist in.
• building agentic systems f.
• rom scratch.
• Assist in troubleshooting and resolving issues related to generative AI models and their implementations.
• Contribute to writing and maintaining clear technical documentation.
• Currently studying a.
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• A foundational.
• understanding of machine learning concepts and the Software Development Life Cycle (SDLC).
• Good programming skills in Python., and ideally some familiarity with C++ or other languages used in ML applications.
• An awareness of Generative AI concepts and curiosity about real-world AI applications.
• Some exposure to LLM APIs.
• such as OpenAI or Hugging Face through coursework, projects, or self-study.
• Good communication and interpersonal skills to effectively work with team members.
• A basic understanding of REST APIs and git version control; familiarity with CI/CD and MLOps principles is a plus.
• Any exposure to cloud platforms (AWS, GCP, or Azure) is a plus.
• Some familiarity with Docker and containerization concepts is a plus.
• This is your chance to build your career in a growing data-driven and AI industry.
• APPLY NOW!.
• Sertis may collect, use, or disclose your personal data or personal data of other persons provided by you in order to carry out your recruitment process. For more information, please refer to our.
• Recruitment Privacy Notice.

ทักษะ:

Agile Development, Recruitment, YouTube, Python, Kafka, Scala, Java, SQL

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• In Agoda's Back End Engineering department, we build the scalable, fault-tolerant systems and APIs that host our core business logic. Our systems cover all major areas of our business: inventory and pricing, product information, customer data, communications, partner data, booking systems, payments, and more. These mission-critical systems change frequently with dozens of releases per day, so we must employ state-of-the-art CI/CD and testing techniques in order to make sure everything works without any downtime. We also ensure that our systems are self-healing, responding gracefully to extreme loads or unexpected input. In order to accomplish this, we use state-of-the-art languages like Scala and Go, data technologies like Kafka and Aerospike, and agile development practices. Most importantly though, we hire great people from all around the world and empower them to be successful. Whether it's building new projects like Flights and Packages or reimagining our existing business, you'll make a big impact as part of the Back End Engineering team.
• The Opportunity.
• We are seeking a Principal Engineer to drive innovation across our AI-powered data experience and platform infrastructure.
• This role combines.
• leading the development of AI-powered data querying.
• enabling users to ask business questions in natural language and receive actionable insights .
• while shaping the evolution of our data quality tools, and analytical engines.
• such as StarRocks.
• As a senior technical leader, you will operate across AI, data infrastructure, and reliability domains, driving high-impact initiatives and serving as a key technical authority across the organization.
• This position is based in Bangkok, Thailand. (Relocation support is provided).
• Lead the development of.
• AI-powered data querying solutions., enabling users to ask business questions in natural language and receive actionable insights.
• Architect and develop scalable data quality tools.
• and frameworks to ensure reliable and trustworthy data.
• Act as a hands-on technical leader, tackling complex challenges.
• across AI query engines, data quality systems, and analytical engines.
• Collaborate with TPMs and stakeholders to define and.
• drive the technical vision and roadmap.
• for AI-driven querying, query engines, and data quality tools.
• Mentor engineers and raise standards.
• across data quality & governance tools, query engines, and the broader data platform.
• 10+ years.
• of experience in software engineering, data engineering, or related fields.
• SQL and large-scale data systems.
• Modern analytical databases / data warehouses.
• (e.g., StarRocks, Snowflake, BigQuery, ClickHouse).
• Backend development.
• (e.g., Python, Java, Scala or similar).
• AI/LLM-based applications.
• (e.g., text-to-SQL, conversational interfaces, cursor, copilots).
• Data platforms or.
• analytical infrastructure at scale.
• Strong understanding of.
• data modeling, query execution, and performance optimization.
• Proven ability to.
• lead cross-team, high-impact technical initiatives.
• Ability to navigate between.
• deep hands-on work and strategic technical leadership.
• Excellent communication skills with both technical and non-technical stakeholders.
• Experience with.
• text-to-SQL systems.
• or AI-driven data interfaces.
• Experience implementing or scaling.
• analytical engines.
• such as StarRocks.
• Background in.
• data observability, quality, or governance frameworks.
• Experience with tools like.
• dbt, Airflow, Spark, or similar.
• Bengaluru.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ประสบการณ์:

6 ปีขึ้นไป

ทักษะ:

Cloud Computing, Architecture, Postgre SQL, Automation, Leadership Skill

ประเภทงาน:

งานประจำ

• AI & Advanced Analytics Enablement.
• Lead the design, development, and deployment of enterprise AI, Machine Learning, and Generative AI solutions to support business transformation (e.g., pricing, promotion, automation, recommendation, demand forecasting, customer insights, and intelligent decision support).
• Build and manage scalable data pipelines supporting AI/ML model training, inference, feature engineering, Feature Store, RAG knowledge bases, and LLM applications.
• Develop reusable datasets, AI-ready data products, feature engineering pipelines, and semantic data models for AI Engineers, Data Scientists, and Business Analytics teams.
• Partner closely with AI Engineers to design, deploy, productionize, and scale AI/ML models, LLM applications, Agentic AI, AI Chatbots, Recommendation Systems, and Mobile AI applications.
• Design and maintain data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise systems, APIs, databases, files, event streams, IoT devices, and third-party platforms.
• Develop scalable data pipelines supporting document ingestion, embedding generation, metadata management, vector indexing, and retrieval workflows for RAG applications.
• Identify opportunities to embed AI into business workflows and operational decision-making to improve efficiency, customer experience, and business value.
• Data Platform & Engineering Leadership.
• Own end-to-end enterprise data architecture from source systems to Data Lake, Lakehouse, Data Warehouse, Feature Store, Semantic Layer, and AI-serving layers.
• Design, develop, and optimize scalable ETL/ELT pipelines supporting batch, micro-batch, streaming, and near real-time data processing.
• Design and maintain workflow orchestration for enterprise data pipelines using Databricks Workflows, Apache Airflow, or equivalent orchestration frameworks.
• Develop enterprise-scale Big Data solutions using Apache Spark and distributed computing frameworks.
• Design scalable logical and physical data models while optimizing database architecture for performance, scalability, reliability, and cost efficiency.
• Ensure enterprise data quality, governance, lineage, metadata management, observability, security, and compliance across data platforms.
• Implement automated data validation, monitoring, logging, alerting, and observability to ensure production-grade data reliability.
• Optimize SQL queries, Spark workloads, partitioning strategies, storage formats, and compute resources for maximum performance and cost efficiency.
• Analyze complex technical issues, identify root causes, troubleshoot production problems, and recommend infrastructure and platform improvements.
• Select, evaluate, and integrate modern data engineering tools, cloud technologies, and AI platform frameworks to support evolving business needs.
• Continuously evaluate emerging technologies in Big Data, Lakehouse Architecture, Data Platform Engineering, Cloud Computing, and AI Platform Engineering.
• AI Platform & Infrastructure.
• Build and maintain enterprise AI data infrastructure supporting LLM, RAG, Agentic AI, AI Chatbots, Recommendation Engines, Intelligent Search, and Intelligent Automation platforms.
• Design and implement scalable AI data pipelines supporting batch, streaming, vector search, embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures.
• Design scalable APIs, data services, and integration layers connecting AI applications with enterprise systems and digital platforms.
• Collaborate with AI Engineers to prepare high-quality datasets for LLM fine-tuning, prompt engineering, model evaluation, inference, and continuous model improvement.
• Support deployment and operationalization of AI products using DataOps, MLOps, CI/CD, containerization, and modern software engineering practices.
• Drive continuous improvements in platform scalability, availability, security, observability, resilience, and operational efficiency.
• Team Leadership & Capability Building.
• Lead, mentor, and develop a high-performing team of Data Engineers, AI Engineers, and Analytics professionals.
• Foster engineering excellence through best practices in architecture design, coding standards, testing, code reviews, deployment, technical documentation, and software engineering.
• Drive architecture reviews, technical design reviews, engineering governance, and platform standardization across the engineering organization.
• Define engineering standards, technical roadmaps, platform architecture, and technology strategy aligned with business objectives.
• Collaborate closely with Product Owners, Business Stakeholders, AI Engineers, Data Scientists, Solution Architects, Infrastructure, and DevOps teams.
• Provide hands-on technical leadership with a strong engineering mindset and willingness to troubleshoot complex production systems.
• Promote continuous learning, knowledge sharing, innovation, and adoption of emerging technologies across the engineering team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Engineering, Management Information Systems, or a related field.
• 6+ years of experience in Data Platform Engineering, Data Engineering, Big Data, or AI Platform development, with experience leading engineering teams.
• Strong experience designing and implementing enterprise-scale Data Lake, Lakehouse, Data Warehouse, or Modern Data Platform architectures.
• Expert proficiency in SQL, Databricks SQL, PostgreSQL, database design, and query performance optimization.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, Spark SQL, Unity Catalog, and distributed data processing.
• Strong experience designing and developing scalable ETL/ELT pipelines and workflow orchestration.
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or equivalent.
• Experience building enterprise-scale data platforms supporting AI/ML, Advanced Analytics, and Generative AI applications.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Leadership Skill, Python

ประเภทงาน:

งานประจำ

• Location of CP AXTRA (Head Office) 3-4 Days: https://share.google/V5Q7MuC44FS341Xhx.
• Location of CP AXTRA Lotus's (Nawamin Office) 1 day: https://maps.app.goo.gl/6cHYiNFfwE8EqrFU6.
• Working style.
• 4-5 Days at the office + work from anywhere.
• Accompany senior management on store visits on Saturdays (half-day or full-day, not every week.
• AI & Advanced Analytics Enablement.
• Lead the design, development, and deployment of enterprise AI, Machine Learning, and Generative AI solutions to support business transformation (e.g., pricing, promotion, automation, recommendation, demand forecasting, customer insights, and intelligent decision support).
• Build and manage scalable data pipelines supporting AI/ML model training, inference, feature engineering, Feature Store, RAG knowledge bases, and LLM applications.
• Develop reusable datasets, AI-ready data products, feature engineering pipelines, and semantic data models for AI Engineers, Data Scientists, and Business Analytics teams.
• Partner closely with AI Engineers to design, deploy, productionize, and scale AI/ML models, LLM applications, Agentic AI, AI Chatbots, Recommendation Systems, and Mobile AI applications.
• Design and maintain data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise systems, APIs, databases, files, event streams, IoT devices, and third-party platforms.
• Develop scalable data pipelines supporting document ingestion, embedding generation, metadata management, vector indexing, and retrieval workflows for RAG applications.
• Identify opportunities to embed AI into business workflows and operational decision-making to improve efficiency, customer experience, and business value.
• Data Platform & Engineering Leadership.
• Own end-to-end enterprise data architecture from source systems to Data Lake, Lakehouse, Data Warehouse, Feature Store, Semantic Layer, and AI-serving layers.
• Design, develop, and optimize scalable ETL/ELT pipelines supporting batch, micro-batch, streaming, and near real-time data processing.
• Design and maintain workflow orchestration for enterprise data pipelines using Databricks Workflows, Apache Airflow, or equivalent orchestration frameworks.
• Develop enterprise-scale Big Data solutions using Apache Spark and distributed computing frameworks.
• Design scalable logical and physical data models while optimizing database architecture for performance, scalability, reliability, and cost efficiency.
• Ensure enterprise data quality, governance, lineage, metadata management, observability, security, and compliance across data platforms.
• Implement automated data validation, monitoring, logging, alerting, and observability to ensure production-grade data reliability.
• Optimize SQL queries, Spark workloads, partitioning strategies, storage formats, and compute resources for maximum performance and cost efficiency.
• Analyze complex technical issues, identify root causes, troubleshoot production problems, and recommend infrastructure and platform improvements.
• Select, evaluate, and integrate modern data engineering tools, cloud technologies, and AI platform frameworks to support evolving business needs.
• Continuously evaluate emerging technologies in Big Data, Lakehouse Architecture, Data Platform Engineering, Cloud Computing, and AI Platform Engineering.
• AI Platform & Infrastructure.
• Build and maintain enterprise AI data infrastructure supporting LLM, RAG, Agentic AI, AI Chatbots, Recommendation Engines, Intelligent Search, and Intelligent Automation platforms.
• Design and implement scalable AI data pipelines supporting batch, streaming, vector search, embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures.
• Design scalable APIs, data services, and integration layers connecting AI applications with enterprise systems and digital platforms.
• Collaborate with AI Engineers to prepare high-quality datasets for LLM fine-tuning, prompt engineering, model evaluation, inference, and continuous model improvement.
• Support deployment and operationalization of AI products using DataOps, MLOps, CI/CD, containerization, and modern software engineering practices.
• Drive continuous improvements in platform scalability, availability, security, observability, resilience, and operational efficiency.
• Team Leadership & Capability Building.
• Lead, mentor, and develop a high-performing team of Data Engineers, AI Engineers, and Analytics professionals.
• Foster engineering excellence through best practices in architecture design, coding standards, testing, code reviews, deployment, technical documentation, and software engineering.
• Drive architecture reviews, technical design reviews, engineering governance, and platform standardization across the engineering organization.
• Define engineering standards, technical roadmaps, platform architecture, and technology strategy aligned with business objectives.
• Collaborate closely with Product Owners, Business Stakeholders, AI Engineers, Data Scientists, Solution Architects, Infrastructure, and DevOps teams.
• Provide hands-on technical leadership with a strong engineering mindset and willingness to troubleshoot complex production systems.
• Promote continuous learning, knowledge sharing, innovation, and adoption of emerging technologies across the engineering team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Engineering, Management Information Systems, or a related field.
• 6+ years.
• of experience in.
• Data Platform Engineering, Data Engineering, Big Data, or AI Platform development,.
• with experience leading engineering teams.
• Strong experience designing and implementing enterprise-scale Data Lake, Lakehouse, Data Warehouse, or Modern Data Platform architectures.
• Expert proficiency in SQL, Databricks SQL, PostgreSQL, database design, and query performance optimization.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, Spark SQL, Unity Catalog, and distributed data processing.
• Strong experience designing and developing scalable ETL/ELT pipelines and workflow orchestration.
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or equivalent.
• Experience building enterprise-scale data platforms supporting AI/ML, Advanced Analytics, and Generative AI applications.
• Experience with LLM, RAG, AI Chatbots, Agentic AI, Vector Databases, Embedding Pipelines, Feature Store, or Recommendation Systems is highly preferred.
• Experience integrating enterprise applications through REST APIs, event-driven architectures, and microservices.
• Strong understanding of Data Governance, Data Quality, Data Lineage, Metadata Management, Data Security, and Data Observability.
• Experience with Azure, AWS, or Google Cloud Platform is preferred.
• Experience with Git, Docker, Kubernetes, CI/CD, DataOps, MLOps, MLflow, or Infrastructure as Code is an advantage.
• Retail, Wholesale, or E-Commerce industry experience is highly preferred.
• Proven track record in delivering enterprise AI platforms, data platforms, or large-scale analytics solutions.
• Strong analytical thinking, problem-solving, communication, stakeholder management, and leadership skills.
• Passion for building scalable engineering platforms, mentoring teams, and delivering business impact through data and AI.
• CP AXTRA | Lotus's.
• CP AXTRA Public Company Limited.
• Nawamin Office: Buengkum, Bangkok 10230, Thailand.
• By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy.".

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Product Development, Postgre SQL, Automation, Javascript, Kubernetes

ประเภทงาน:

งานประจำ

• Design, develop, and fine-tune Generative AI solutions using leading LLMs such as GPT-4o, Claude (Anthropic), Gemini, and open-source models (LLaMA, Mistral, etc.).
• Build and maintain End-to-End AI Chatbot systems from prompt engineering and LLM integration to deployment and monitoring.
• Develop production-grade RAG (Retrieval-Augmented Generation) Chatbot pipelines integrating vector search, document chunking, embedding models, and LLM inference.
• Implement and manage Vector Storage solutions using FAISS, Qdrant, Weaviate, Pinecone, or similar technologies for semantic search and knowledge retrieval.
• Design and deploy Agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, or custom multi-agent orchestration workflows.
• Integrate AI capabilities with enterprise APIs, databases, and internal platforms via LangChain, LlamaIndex, or equivalent tooling.
• Stay current with rapidly evolving AI/ML tools including Hugging Face, Ollama, vLLM, OpenAI APIs, Vertex AI, AWS Bedrock, and Azure OpenAI Service.
• AI Product Development & MLOps.
• Own the end-to-end AI product lifecycle: requirements gathering, model selection, development, testing, deployment, and continuous improvement.
• Build and manage scalable AI inference pipelines with performance monitoring, logging, and cost optimization.
• Design prompt engineering strategies, evaluation frameworks, and guardrails for safe and reliable LLM outputs.
• Implement CI/CD workflows for AI models using MLflow, DVC, or similar MLOps tools.
• Collaborate with Data Science and Engineering teams to productionize machine learning and AI models.
• Identify opportunities to embed AI capabilities into business workflows, automation, and decision-making processes.
• Data Engineering & Platform (Foundational Awareness).
• Understand the fundamentals of data pipeline concepts (ETL/ELT, batch and streaming) to effectively collaborate with Data Engineering teams.
• Able to read, query, and work with data from common platforms such as Databricks, Snowflake, BigQuery, or PostgreSQL.
• Understand data flow from source systems to data warehouses/lakehouses to inform AI model inputs and outputs.
• Familiar with vector database concepts and embedding pipelines sufficient to configure and use them in AI projects.
• Capable of communicating data requirements clearly to Data Engineers when building AI features or knowledge bases.
• Collaboration & Innovation.
• Partner with product managers, business stakeholders, and engineers to translate business requirements into AI solutions.
• Contribute to and promote best practices for AI development, testing, documentation, and responsible AI usage.
• Mentor junior engineers and share knowledge on emerging AI tools, frameworks, and research.
• Evaluate and adopt new AI/ML technologies and frameworks to keep the team at the forefront of innovation.
• Effectively manage multiple priorities and deliver high-quality solutions independently and as part of a team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, or a related field.
• 3+ years of hands-on experience in AI/ML engineering with a focus on Generative AI and NLP applications.
• Proven experience building Generative AI solutions using GPT-4o, Claude (Anthropic), Gemini, or equivalent LLMs this is a must.
• Hands-on experience with RAG Chatbot development: embedding pipelines, chunking strategies, retrieval tuning, and LLM response generation.
• Proficiency in Vector Storage technologies such as FAISS, Qdrant, Weaviate, Pinecone, or ChromaDB.
• Experience building End-to-End Chatbot systems including intent handling, context management, multi-turn dialogue, and API integration.
• Practical knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI, or similar) for building multi-step, tool-using AI agents.
• Strong Python programming skills Python (required), SQL, JavaScript/TypeScript (a plus).
• Familiarity with popular AI/ML tools and platforms: LangChain, LlamaIndex, Hugging Face, Ollama, vLLM, OpenAI SDK, Vertex AI, AWS Bedrock, or Azure OpenAI.
• Experience with prompt engineering techniques including few-shot prompting, chain-of-thought, structured output, and function calling.
• Ability to evaluate LLM outputs using metrics and frameworks (RAGAS, TruLens, or custom eval pipelines).
• AI Frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI, Hugging Face Transformers.
• LLM Platforms: OpenAI (GPT-4o), Anthropic Claude, Google Gemini, Meta LLaMA, Mistral.
• Vector Databases: FAISS, Qdrant, Weaviate, Pinecone, ChromaDB.
• Cloud & Data: AWS / GCP / Azure AI services, Databricks, Snowflake, PostgreSQL.
• MLOps: MLflow, DVC, Docker, Kubernetes (a plus).
• Big Data: Apache Spark, Kafka (a plus).
• Experience in Retail or E-Commerce AI applications (e.g., recommendation engines, pricing AI, conversational commerce).
• Familiarity with fine-tuning and PEFT techniques (LoRA, QLoRA) for LLMs.
• Knowledge in machine/statistical learning, computer vision, or time series forecasting.
• Experience with AI safety, hallucination mitigation, and responsible AI practices.
• Contributions to open-source AI projects or published AI research.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Software Development, Recruitment, Assurance, Docker, English

ประเภทงาน:

งานประจำ

Who We Are Located in the heart of Bangkok's Phrom Phong District, Sertis is ASEAN's leading Data and AI engineering and solutions company. Since 2014, our advanced solutions and products have powered over 400 enterprise Data and AI deployments at the region's leading companies and conglomerates. We are also a member firm of Andersen Consulting, a global consulting practice integrating business strategy, digital transformation, and AI-driven technology solutions with Andersen Global's world-class expertise. What We Do Sertis provides both productized and bespoke AI and Data solutio ...

ประสบการณ์:

7 ปีขึ้นไป

ทักษะ:

Architecture, Recruitment, TypeScript, Javascript, YouTube, English, Thai

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• As our Staff Front-End Engineer, you will design and build AI-driven chat experiences that power Agoda's AI Assistant, trip planning and discovery, customer support flows, and proactive recommendations. You'll work closely with engineers, data scientists, and product managers to define, build, and scale the next generation of AI solutions that make travel planning more intuitive, personalized, and effortless for millions of customers worldwide.
• We're looking for a visionary Front-End architect with a strong hands-on mentality integrating innovative AI capabilities and rapidly validating ideas through experimentation. You will create measurable impact on traveler experience and business outcomes, while upholding Agoda's standards for privacy, reliability, and the responsible use of AI.
• Why Agoda & Why Bangkok?.
• Global Engineering, Global Impact: Join a high-energy, multilingual and multicultural engineering team in Bangkok driving innovation across regions.
• Vibrant Bangkok HQ: Work in a tech-centric city with a thriving expat community, beautiful culture, and world-famous cuisine.
• English-First: Work and collaborate in English no Thai required!.
• World-class relocation and family support are offered.
• Your Role & Impact.
• Spearhead architecture and system design of Agoda's next-gen front end systems.
• Drive best-in-class performance, accessibility, and usability.
• Mentor and subject-matter-expert for the FE engineering team.
• Influence stakeholders in the Product and Business teams.
• Set technical standards and ensure scalability.
• What You'll Bring.
• 8+ years' experience building and leading rich web applications at scale.
• Deep mastery of JavaScript/TypeScript and modern frameworks (React, Next, Vue).
• Portfolio of building robust, high-performance SPA/SSR front ends and core web vitals.
• Strong background in team leadership, system design, and stakeholder influence.
• Bonus: Experience with A/B experimentation, international exposure, or travel/e-commerce products.
• What We Offer.
• Visa, flight & moving package for you and family.
• Temporary housing, settling-in help, and expat community onboarding.
• Spousal/partner and family adaptation support.
• International healthcare benefits.
• Hybrid remote/Bangkok HQ model.
• Learning and development budget, hackathons, and internal tech communities.
• https://careersatagoda.com/agodans-in-bangkok/.
• https://medium.com/agoda-engineering.
• This position is based in Bangkok, Thailand (Relocation Provided).
• bangalore.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Architecture, Automation, English

ประเภทงาน:

งานประจำ

• Understand customer business requirements and identify opportunities for UiPath, RPA, AI, and Agentic AI solutions.
• Design and propose suitable automation and AI solutions based on customer needs.
• Conduct solution presentations, product demonstrations, workshops, and POCs.
• Prepare technical proposals, solution architecture, and supporting documentation.
• Collaborate with sales, vendors, partners, and technical teams throughout the presales process.
• Support RFP/RFQ responses and solution proposals.
• Stay updated on emerging technologies in RPA, Generative AI, Agentic AI, and intelligent automation.
• Experience & Requirements.
• Minimum 5 years of experience in Presales, Solution Consulting, Solution Architecture, or Technical Sales.
• Experience with UiPath and strong knowledge of Agentic AI.
• Exposure to Agentic AI, Generative AI, AI Agents, LLMs, or intelligent Automation solutions is highly preferred.
• Strong understanding of automation concepts and ability to translate business requirements into technical solutions.
• Experience in conducting product demonstrations, presentations, workshops, and POCs.
• Strong communication, presentation, and customer-facing skills.
• Experience working in an IT Vendor, System Integrator (SI), or IT Distributor environment is preferred.
• Good command of English.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Software Development, Automation, Kubernetes, TypeScript, node.js

ประเภทงาน:

งานประจำ

• Build and integrate AI features into internal tools, microservices, and automation workflows.
• Develop LLM powered assistants, RAG systems, and knowledge tools using models like Claude, GPT, and Gemini.
• Create APIs, pipelines, and services that make AI reliable, scalable, and safe.
• Improve developer productivity through AI augmented coding, testing, and documentation tools.
• Contribute to the company's AI roadmap and help identify high impact AI opportunities.
• Evaluate new AI tools, models, and platforms and recommend what we should adopt.
• Help define best practices for prompt engineering, model usage, and safe deployment.
• Support teams in adopting AI responsibly, including training, documentation, and internal guidelines.
• Work with architects to ensure AI systems follow governance, auditability, and data handling standards.
• Partner with product, engineering, and operations teams to translate business needs into AI solutions.
• Lead design discussions for new AI powered features and internal platforms.
• Help build a culture of experimentation and continuous improvement around AI.
• Capabilities.
• At least 5 years of software engineering experience.
• Proven experience working on agentic applications with the ability to articulate the tradeoffs between different approaches.
• Strong skills in Python, Node.js/TypeScript, or Go. Good awareness of SQL.
• Hands-on experience with LLM APIs and context engineering.
• Familiarity leveraging vector databases, RAG pipelines and memory systems.
• Experience building APIs, microservices, or event driven systems.
• Experience with enterprise SDLC tooling including version control, CI/CD systems, testing methodologies as they pertain to generative and agentic applications.
• Interest in AI strategy, evaluation, and responsible AI practices.
• Curiosity, problem solving mindset, and willingness to explore new tools.
• Experience with delivering applications to Kubernetes runtime environments a plus.
• Experience using workflow engines, automation, or internal developer platforms.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Agile Development, Automation, Scrum

ประเภทงาน:

งานประจำ

• Our company is currently in the process of revolutionizing an internal IT industry to optimize and improve our customer journey throughout our system of which it supports from the Point of Sales to the gigantic ERP system.
• As Tooling and Innovation Engineer, your role is providing innovation/technologies/tools evaluation, design, implement and support for just in time solutions align with rapid business changes. Tools & Innovation are integrated applications with business operation to optimize and efficient. It can be both create a new system or add-on ...
• Tooling and Innovative Engineer also develop solutions for improve all organization's operations for replacing manpower with RPA (Robotic Process Automation) to making Hyper Automation Organization. For example, Integration between systems, Reconciliation, Issue Analytical Chatbot for improve quality checking list, Automation process / job for reducing manpower and etc.
• Your job is working with many departments in organization for transform manually operations to be automation including provide guidance for their able develop automation with our automation platforms. We are using Agile methodology for managing planning and delivery cycle.
• Design / Implement & Unit Testing / Testing / Support applications or services for improving organization's process.
• Provide Technology / Tools evaluation for selecting the best fit or Innovation / Tool / RPA.
• Co-ordinate / Participate in UAT for user testing our solutions.
• Create design documents and/or manual (if needed).
• Coaching and Mentoring team members.
• More than full stack developer; able to do basic DevOps, Testing and Requirement gathering.
• Able to identify gaps for defining initiative for team level improvement.
• Delivery cycle with agile methodologies.
• Back up team leader for managing team.
• Development by AI Agent Assistance (SDD or Vibe Code).
• Key Requirements.
• Bachelor's degree in IT related and experience more than 6 years in Software development.
• Flexible, Adaptative and Open mind for any new challenges and changes.
• Innovative and think outside to box for mix & matched on solutions.
• Business driven over individual interest.
• Teamwork and transparent.
• At least 2 years in senior position or equivalent.
• At least 3 years on node.js and TypeScript either server or client-side development.
• At least 3 years on Git for source control.
• At least 2 years on TDD (Test Driven Development) and unit testing framework such as jasmine, etc.
• At least 2 years on either SQL or noSQL.
• At least 1 years on AI Agent Assistance development (SDD or Vibe Code).
• Experienced on Agile development any Scrum / Kanban / ScrumBan.
• Experienced on Code reviewer and Code healthiness analysis for eliminate code smell.
• Experienced on CI/CD Concept such as Jenkins.
• Experienced on IDE such as Visual Studio Code, IntelliJ and etc.
• Experienced on Web Client JS framework such as Angular, React, Vue and etc. As a plus.
• Experienced on Groovy language as a plus.
• Experienced on JIRA Plugin as a plus.
• Experienced on Salesforce APEX coding as a plus.
• Experienced on Jenkins pipeline as a plus.
• Experienced on RPA (Such as UI Path, Selenium, WebDriver and etc.) as a plus.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

OCR

ประเภทงาน:

งานประจำ

The Senior AI Engineer position involves designing and implementing scalable AI systems for enterprise applications, including Machine Learning, Computer Vision, Generative AI, and AI Agent platforms. Key duties encompass developing production-ready AI services with optimized performance and cost efficiency. The role requires building AI agents from single-purpose to multi-step, tool-using systems with appropriate autonomy and safeguards. Engineers will integrate ML and generative AI models through APIs and microservices, deploy AI workloads on cloud and on-premise GPU infrastructu ...

ประสบการณ์:

4 ปีขึ้นไป

ทักษะ:

Automation, TypeScript, Python, Java, English

ประเภทงาน:

งานประจำ

• Build evaluation suites for LLM and ML features: curated test sets, scoring against reference answers, LLM-as-judge where it is justified, and human review where it is not.
• Define what "good enough" means with the delivery team before launch, in numbers a client can accept, and hold releases to it.
• Test retrieval pipelines end to end, covering chunking and indexing, retrieval quality, grounding of the final answer, and behaviour when the right document is simply n ...
• Write regression tests that tolerate non-deterministic output, using semantic similarity, structured-output validation, tolerance bands, and repeated sampling rather than exact string matching.
• Cover failure modes that matter to clients: hallucination, prompt injection through user or document content, leakage of data across tenants or sessions, refusal and over-refusal, and degradation on Thai-language input.
• Track cost and latency alongside accuracy, so that a quality improvement that triples token spend is visible before it ships.
• Detect drift after release by comparing production samples against the baseline, and raise it early rather than after the client does.
• Design and maintain automated test suites for APIs, services, data pipelines, and web applications built for client projects.
• Run tests in CI, keep them fast and stable, and treat a flaky suite as a defect in its own right.
• Set the test strategy at the start of an engagement: what gets automated, what stays manual, what the exit criteria are, and what evidence the client will receive.
• About you.
• 4-5 years in test automation, QA engineering, or software engineering with substantial testing ownership.
• Strong programming ability in Python, or in TypeScript or Java with the willingness to work primarily in Python.
• Hands-on experience testing an LLM or ML-based product in production or close to it.
• Practical command of at least one automation framework such as Pytest, Playwright, Cypress, or RestAssured, and experience running suites in CI.
• Working knowledge of API and data testing, including SQL and validating data through a pipeline.
• The judgement to decide what deserves automation and what does not, and to say so when a suite is producing noise rather than signal.
• Clear written and spoken communication in Thai and English.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Electrical Engineering, Production Engineering, Kubernetes, TensorFlow, Python, Docker

ประเภทงาน:

งานประจำ

• Amity, through its AI Research and Application Center, is advancing the frontier of applied AI research across natural language processing, large language models, agentic systems and generative AI. We build intelligent products that serve millions of users and partner organisations across Southeast Asia and Europe. Our research engineers sit at the intersection of scientific inquiry and production engineering - discovering new methods, validating them rigorously, and shipping them into real-world products.
• As an AI Research Engineer at Amity.
• AI Research and Application Center.
• you will own ambitious research goals while ensuring that breakthroughs translate into scalable, production-grade systems.
• Identify high-impact research problems, formulate hypotheses, design experiments and advance the state of the art in areas aligned with the lab's mission.
• Publish findings at top-tier conferences and top-tier leaderboard and contribute to the broader AI research community.
• Bridge the gap between research prototypes and production systems, ensuring novel methods are robust, efficient and deployable at scale.
• Shape the lab's research roadmap and propose initiatives that create measurable business and societal value.
• Mentor junior researchers and engineers, fostering a culture of scientific rigour and collaborative innovation.
• Research & Experimentation.
• large language models., NLP, computer vision, reinforcement learning, generative models, agentic AI or multimodal learning.
• Design and run rigorous experiments - including ablation studies, benchmark evaluations and statistical analyses - to validate new methods and architectures.
• Survey, reproduce and extend state-of-the-art results from recent literature; maintain a reading group culture within the team.
• Develop novel algorithms, model architectures and training strategies that push performance boundaries on real-world tasks.
• Model Development & Optimisation.
• Design, train and fine-tune large-scale deep learning models (LLMs, diffusion models, multi-modal models) using modern frameworks such as PyTorch, TRL, Unsloth or verl. (Reinforcement Learning Experience is plus).
• Optimise model performance through techniques such as knowledge distillation, quantisation, pruning, mixed-precision training and efficient attention mechanisms.
• Build and improve training infrastructure for distributed, large-scale model training across GPU/TPU clusters.
• Develop evaluation frameworks and metrics to systematically measure model quality, safety and robustness.
• Applied Research & Productionisation.
• Translate research outcomes into production-ready features - building proof-of-concepts (PoCs), prototypes and scalable AI services.
• Design and operate RAG pipelines (ingestion, chunking, embeddings, hybrid search, re-rankers) with vector databases (pgvector, Pinecone, Weaviate, OpenSearch) to support retrieval-augmented applications.
• Architect and ship LLM-powered agents and chatbots using agentic patterns (tool/function calling, planning, memory, multi-agent orchestration) with robust safety and fallback mechanisms.
• Collaborate with product and engineering teams to integrate AI capabilities into customer-facing platforms via APIs and microservices.
• Data & Infrastructure.
• Curate, clean and build high-quality datasets for pre-training, fine-tuning and evaluation; design data pipelines for continuous data collection and annotation.
• Implement and maintain scalable ML infrastructure using Docker, Kubernetes, CI/CD and experiment-tracking tools (MLflow, Weights & Biases, or similar).
• Monitor deployed models, design automated retraining pipelines and ensure ongoing model quality through observability and alerting.
• Knowledge Sharing & Community.
• Author technical papers, internal reports and blog posts that communicate research findings to both technical and non-technical audiences.
• Present research at internal seminars, external conferences and community meetups.
• Contribute to open-source projects and public benchmarks to enhance Amity's visibility in the research community.
• Required.
• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering or a related quantitative field.
• 3+ years of hands-on experience in AI/ML research or research engineering, with demonstrated ability to design experiments, analyse results and iterate on methods.
• At least one first-author or co-author publication at a recognised venue (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, AAAI, or equivalent), or equivalent demonstrated research output (patents, technical reports, significant open-source contributions).
• Strong proficiency with Python and modern deep learning frameworks (PyTorch, JAX, or TensorFlow); solid understanding of model architectures (Transformers, diffusion models, GNNs) and training techniques (RLHF, DPO, SFT, pre-training).
• Ability to write clean, maintainable, production-quality code; familiarity with software engineering best practices (version control, code review, testing, CI/CD).
• Strong grounding in linear algebra, probability, statistics, optimisation and information theory.
• Experience designing agentic architectures (tool/function calling, planning, memory, multi-agent orchestration via frameworks such as LangChain, LlamaIndex, AutoGen or CrewAI).
• Hands-on experience with retrieval-augmented generation pipelines, embedding models, hybrid search and vector databases.
• Experience with large-scale distributed training across multi-GPU/TPU environments (DeepSpeed, FSDP, Megatron-LM or similar).
• Working knowledge of cloud platforms (AWS, GCP or Azure) and ML operations tooling (MLflow, W&B, Kubeflow).
• Active contributions to well-known AI/ML open-source projects or libraries.
• Excellent written and verbal communication skills; ability to distill complex research into clear recommendations for diverse stakeholders.
• At Amity Solutions, we are dedicated to creating a dynamic and supportive work environment that prioritizes growth, learning, and inclusivity. As an equal opportunity employer, we welcome applicants from all backgrounds, embracing diversity in ethnicity, gender, disability, religion, belief, sexual orientation, and age. Join our Bangkok team to enjoy a wide range of benefits as we innovate and grow together.
• Discover more about our team values, benefits, and career opportunities at Amity Solutions Bangkok on our.
• official website.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Architecture, Recruitment, Automation, Assurance

ประเภทงาน:

งานประจำ

• Partner with business stakeholders to identify, assess, and prioritize AI opportunities that address real business challenges.
• Act as a trusted advisor on AI capabilities, feasibility, implementation approaches, and expected business outcomes.
• Help stakeholders translate ideas and business requirements into practical AI-enabled solutions with clear value propositions, implementation considerations, and success criteria.
• Support AI initiatives from ideation through adoption, ensuring alignment between business objectives and technical implementation.
• Enterprise AI Solution Delivery.
• Lead end-to-end AI solution delivery from problem definition, solution design, implementation planning, development, integration, deployment, and operation.
• Deliver AI capabilities that can be reused and scaled across multiple business units.
• Translate business needs into practical AI solution options, including architecture, implementation approaches, dependencies, risks, and delivery trade-offs.
• Ensure AI solutions are delivered with measurable business impact and clearly defined success metrics.
• AI Solution Architecture & System Design.
• Act as the AI engineering specialist for enterprise AI initiatives, advising stakeholders on AI architecture, solution feasibility, implementation strategy, and technology selection.
• AI services.
• AI agents.
• Knowledge retrieval systems.
• APIs and integrations.
• Workflow orchestration.
• Evaluation and monitoring frameworks.
• Guardrails and fallback mechanisms.
• Define reusable AI engineering patterns, reference architectures, and implementation standards to support enterprise adoption.
• Ensure AI solutions meet standards for scalability, security, reliability, maintainability, observability, and operational readiness.
• Implementation Planning & Technical Delivery.
• Lead technical planning for AI initiatives, including implementation roadmaps, technical dependencies, effort estimation, delivery risks, and release approaches.
• Convert AI concepts into executable implementation plans for engineering teams, vendors, or delivery partners.
• Support technical due diligence, solution feasibility assessment, build-versus-buy analysis, and vendor technical evaluation.
• Drive implementation decisions that balance business value, technical complexity, scalability, and operational sustainability.
• Hands-on Engineering & Implementation.
• Personally contribute to the implementation of critical solution components when required.-Develop prototypes, proof-of-concepts, and production-ready AI solutions.
• Implement or review AI services, APIs, orchestration logic, retrieval pipelines, integrations, automation workflows, and evaluation mechanisms.
• Review technical designs and code to ensure engineering quality, maintainability, security, and alignment to enterprise standards.
• Support troubleshooting and resolution of critical AI production issues.
• Applied AI, GenAI & Machine Learning.
• Prompt engineering.
• AI agent design.
• Retrieval-Augmented Generation (RAG).
• Workflow orchestration.
• Human-in-the-loop design.
• AI evaluation and testing.
• Design AI systems with appropriate quality controls, monitoring approaches, guardrails, fallback strategies, and performance measurement.
• Support implementation, deployment, and integration of machine learning models where applicable.
• Establish evaluation methods and success criteria to ensure AI solutions deliver reliable and measurable outcomes.
• Governance & Responsible AI.
• Ensure AI solutions comply with governance, security, privacy, risk, and Responsible AI requirements.
• Embed governance-by-design principles into AI architectures, including auditability, monitoring, access controls, and human oversight.
• Support AI governance processes by providing technical assessments, architecture reviews, implementation considerations, and risk evaluations.
• Team & Capability Development.
• Mentor and guide AI engineers and technical contributors to strengthen AI engineering capabilities.
• Promote best practices in AI system design, architecture, implementation planning, and engineering excellence.
• Contribute reusable assets, frameworks, technical standards, playbooks, and reference implementations.
• Help establish a strong AI engineering culture focused on production-quality delivery and measurable business outcomes.
• Key Interfaces.
• Business Units and AI Business Champions.
• Technology and Architecture Teams.
• Data and Analytics Teams.
• Security, Risk, Privacy, and Compliance Teams.
• AI Governance Bodies and Steering Committees.
• Vendors, Technology Partners, and Delivery Teams.
• Experience.
• Significant experience in software engineering, enterprise insurance platforms, intelligent automation, or applied AI solutions.
• Proven experience designing, planning, implementing, and operating complex software or AI solutions in enterprise environments.
• Experience leading AI solution architecture, system design, implementation planning, and production delivery.
• Experience working across business and technology functions to deliver measurable business outcomes.
• Experience in regulated or risk-sensitive industries is an advantage.
• Technical Skills.
• Strong software engineering fundamentals with experience building enterprise-grade applications, backend services, APIs, integrations, and distributed systems.
• Practical experience delivering applied AI, Generative AI, intelligent automation, or AI-enabled business solutions into production.
• LLM applications.
• Retrieval-Augmented Generation (RAG).
• Thank you for your job application with Prudential Life Assurance (Thailand) Public Company Limited.
• To align with Prudential Group Employee Privacy Notice, candidate acknowledged the record and usage of candidate's personal details to Prudential Life Assurance (Thailand) Public Company Limited and its business partner for recruitment purpose.
• See more detail https://www.prudential.co.th/corp/prudential-th/en/privacy-notice-staff/.
• Refer to Prudential Life Assurance (Thailand) Public Company Limited's Privacy notice regarding recruitment at https://www.prudential.co.th/corp/prudential-th/th/privacy-notice-staff/, and please be informed that company conducts criminal background checks for all positions during the hiring process.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Software Architecture, Architecture, Kubernetes, TensorFlow, Leadership Skill

ประเภทงาน:

งานประจำ

• Design, develop, and optimize AI / Machine Learning models for business applications.
• Large Language Models (LLMs).
• AI Assistants.
• Chatbots.
• Retrieval-Augmented Generation (RAG) systems.
• Develop predictive models and advanced analytics solutions.
• Design AI workflows, pipelines, and model architectures for enterprise-scale deployment.
• Improve model performance, accuracy, scalability, and reliability.
• Engineering & Infrastructure.
• Develop AI APIs, backend services, and AI-enabled platforms.
• Deploy and manage AI models on cloud infrastructure (AWS, GCP, Azure).
• CI/CD pipelines.
• Model monitoring.
• Version control.
• Governance and compliance.
• Optimize system performance, security, latency, and scalability.
• Integrate AI systems with internal enterprise systems and third-party platforms.
• Collaboration & Leadership.
• Collaborate with Product, Business, Data, and Technology teams to identify AI opportunities.
• Provide technical leadership and recommendations on AI architecture and best practices.
• Research emerging AI technologies and evaluate business applications.
• Mentor junior engineers and support capability development within the team.
• Prepare technical documentation, standards, and operational procedures.
• Bachelor's degree or higher in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, or related fields.
• Minimum 5 years of experience in AI / Machine Learning Engineering.
• Minimum 2 years of experience in Generative AI or Large Language Models (LLMs).
• Proven experience deploying AI systems into production environments.
• Technical Skills.
• Strong proficiency in Python.
• PyTorch.
• TensorFlow.
• Scikit-learn.
• LangChain / LlamaIndex.
• Deep Learning.
• Natural Language Processing (NLP).
• Vector Databases.
• Embedding Models.
• RAG Architecture.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Docker.
• Kubernetes.
• Git.
• CI/CD pipelines.
• Knowledge of enterprise system design and software architecture.
• Preferred Qualifications.
• Experience in AI Governance, AI Security, or Responsible AI.
• Experience developing AI Agents or Autonomous Systems.
• Experience building enterprise AI platforms or AI SaaS products.
• Previous experience as a Technical Lead or Team Lead.
• Contributions to open-source projects, research publications, or innovation initiatives.
• Soft Skills.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Leadership mindset with strong ownership and accountability.
• Ability to work effectively in cross-functional teams.
• Passion for continuous learning and emerging technologies.
• Provident Fund.
• Performance bonus.
• Life insurance.
• Medical insurance.
• Dental insurance.
• etc.
• To apply online please click the 'Apply' button below.
• https://jobs.empeo.com/tkcservices.
• For a confidential discussion about this role please contact.
• Turnkey Communication Services Public Company Limited.
• 44/44 Vibhavadi-Rangsit 60 Yake 18-1-2, Talad Bangkhen, Laksi, Bangkok 10210.
• https://www.tkc-services.com.
• https://www.facebook.com/TurnkeyCommunicationServices.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Google Cloud Platform, Industry trends, Architecture, Kubernetes, VMware

ประเภทงาน:

งานประจำ

• Solution Design & Consulting.
• Analyze customer business and technical requirements.
• Design and recommend HPE HIT & AI solutions, including AI Infrastructure, High-Performance Computing (HPC), Data Center, Hybrid Cloud, Server, and Storage solutions.
• Prepare solution architecture, technical proposals, and scope of work documents.
• Deliver technical presentations and solution demonstrations to customers and partners.
• Pre-sales Support.
• Collaborate closely with the Sales team to identify business opportunities and drive revenue growth.
• Provide technical consultation and solution recommendations to customers and partners.
• Design system configurations and prepare Bill of Materials (BOM) based on customer requirements.
• Conduct product comparison and competitive analysis.
• AI & Data Infrastructure Solutions.
• Provide guidance on AI Infrastructure, GPU Computing, and AI workloads.
• Design solutions supporting Machine Learning (ML), Deep Learning (DL), and Generative AI applications.
• Recommend appropriate server, storage, networking, and software platforms for AI projects.
• Stay updated on emerging AI technologies and industry trends.
• Technical Demonstration & Proof of Concept.
• Conduct Proof of Concept (PoC), product demonstrations, and technical workshops.
• Validate solution feasibility and performance prior to implementation.
• Prepare technical documentation, implementation recommendations, and best practices.
• Vendor & Partner Collaboration.
• Maintain up-to-date knowledge of HPE products, solutions, and technologies.
• Work closely with HPE, technology vendors, and business partners to support customer projects.
• Attend technical training programs and obtain relevant certifications.
• What we're looking for.
• Minimum 2-5 years of experience in Pre-sales Engineering, Systems Engineering, Solution Architecture, or Technical Consulting.
• Experience in Enterprise Infrastructure, Servers, Storage, Networking, Data Center, or Hybrid Cloud solutions.
• Experience with AI Infrastructure, HPC, GPU Computing, or Data Analytics solutions is highly preferred.
• Strong understanding of HPE Servers, Storage, Networking, and HPE GreenLake solutions.
• Knowledge of AI, Machine Learning, Deep Learning, and Generative AI technologies.
• Familiarity with Virtualization and Cloud technologies such as VMware, Hyper-V, Kubernetes, Containers, AWS, Azure, or Google Cloud Platform.
• Understanding of Data Center Architecture and Enterprise IT Infrastructure.
• Excellent presentation, communication, and interpersonal skills.
• Strong analytical and problem-solving abilities.
• Ability to prepare technical proposals, solution designs, and architecture documentation.
• Capable of working effectively with Sales teams, customers, vendors, and partners.

ทักษะ:

Full Stack

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• Join a team of talented engineers who are passionate about front-end development. Our team is dedicated to building cutting-edge web applications using Typescript, React, and Redux.
• As a Front-End Engineering Manager at Agoda, you will lead a team of talented engineers building scalable, high-performance web applications that power user experiences at global scale. You will work closely with product managers, designers, data scientists, and cross-functional engineering teams to develop user-facing applications and platforms that integrate AI capabilities into Agoda's products at global scale.
• Lead a team of engineers building scalable, reliable, and user-friendly web applications and product experiences.
• Drive the development of front-end and full-stack solutions across core product areas, including selected AI-enabled features and workflows.
• Collaborate with product, design, data, and engineering teams to deliver intuitive and impactful customer or internal user experiences.
• Shape architecture across areas such as state management, SSR, micro-frontends, and API integration.
• Ensure new features, including AI-assisted capabilities where relevant, are performant, maintainable, observable, and production-ready.
• Guide the team in designing interfaces and workflows that surface recommendations, automation, or intelligent product enhancements in a usable and reliable way.
• Improve application quality through engineering best practices including code reviews, testing, experimentation, and continuous delivery.
• Support integration with backend services through REST, GraphQL, WebSockets, and other service interfaces.
• Drive technical decisions around performance, reliability, monitoring, and maintainability in production.
• Mentor engineers and grow team capability in both modern web engineering and evolving product development practices.
• Bring strong experience leading teams building large-scale web applications with React, Angular, or Vue.
• Demonstrate solid hands-on expertise in JavaScript / TypeScript and front-end development.
• Apply strong knowledge of web performance optimization, scalability, and frontend best practices.
• Show experience integrating frontend applications with backend services through REST, GraphQL, or WebSockets.
• Drive strong technical and people leadership, with proven mentoring and coaching ability.
• Collaborate effectively with product, design, and engineering stakeholders.
• Contribute to architectural decisions across SSR, micro-frontends, and state management.
• Operate with a strong understanding of CI/CD, automated testing, and deployment for web applications.
• Communicate clearly and thrive in a fast-paced, collaborative environment.
• Bring exposure to full-stack development and backend technologies such as C#, Kotlin, or Scala.
• Demonstrate familiarity with Agile development methodologies.
• Show experience with mobile web, cross-platform frameworks, or cloud platforms.
• Apply experience with analytics, A/B testing, and SEO for large-scale web products.
• Demonstrate experience building customer-facing products in high-traffic or global-scale environments.
• bangkok.
• LI-Hybrid.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Android, Kotlin, iOS, English

ประเภทงาน:

งานประจำ

• Build and ship mobile features for Android and/or iOS.
• Create simple mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product, design and backend teams to turn complex journeys into usable mobile products.
• Integrate APIs and handle edge cases, loading states, errors and production issues.
• Improve app performance, reliability, crash rate and user experience.
• Support fast product launches, experiments and iterations across mobile journeys.
• Help set high standards for mobile product quality across the app.
• What We're Looking For.
• 3+ years of mobile development experience in Android, iOS or both.
• Strong experience with Kotlin and/or Swift.
• Experience shipping production apps used by real users.
• Strong product sense and attention to mobile UX.
• Able to work with APIs, analytics, crash logs and production feedback.
• Fast, practical and comfortable owning work with limited handholding.
• App links, GitHub, screenshots or examples of shipped work are a strong advantage.
• The Kind of Builder We Want.
• Thinks like a product builder, not just a mobile coder.
• Cares about smooth flows, small details and real user behaviour.
• Can work across ambiguity and ship without waiting for perfect specs.
• Takes production quality personally.
• Honest about what they built directly versus what the wider team delivered.
• This Role Is Not For.
• Developers who only want to build isolated screens.
• People who do not care about UX, performance or reliability.
• Candidates who cannot explain their own contribution clearly.
• People who need heavy guidance for every task.
• Engineers who move slowly in a high-growth environment.
• This role is remote, but candidates must be based in Thailand. We are hiring specifically for this market, so applicants should already be based in Thailand.
• Language.
• English is our main working language across global teams. Strong English communication is required.
• Interview Process.
• Online assessment or practical task.
• Role-specific interview.
• CEO / final round.
• For strong candidates, we aim to complete the process and make an offer within 1 week from the start of the interview process. Candidates who complete assessments quickly will be prioritized.