เงื่อนไขการค้นหา

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Cloud Computing, English, Thai

ประเภทงาน:

งานประจำ

• Engage with customers to identify business needs and challenges.
• Develop practical AI use cases to enhance productivity.
• Design AI adoption plans and create workshop materials.
• Conduct training sessions and hands-on workshops for business users.
• Assist customers in utilizing AI tools like Microsoft 365 Copilot and others.
• Create user guides, prompt examples, and best practices.
• Provide post-training support and track business value from AI adoption.
• Collaborate with sales and technical teams to deliver successful AI projects.
• 2-5 years of experience in consulting, customer success, training, presales, business analysis, or related roles.
• Strong communication and presentation skills.
• Ability to explain technology in simple terms.
• Passion for AI, digital transformation, and business productivity.
• Proficiency in creating clear documents, slides, and workshop materials.
• Eagerness to learn new AI tools and continuously improve.
• Why to apply?.
• Work on real AI projects with leading Thai and international companies.
• Gain expertise in cutting-edge AI tools like Microsoft Copilot, Claude, and Gemini.
• Flexible working hours and hybrid work options.
• Access to training, certifications, and skill development opportunities.
• Be part of a dynamic team driving digital transformation.
• Location: MRT Samyan.
• Join MISO and help businesses turn AI into real business value.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Microsoft Azure, Cloud Computing, Google Cloud Platform, Thai, English

ประเภทงาน:

งานประจำ

• Design and implement Microsoft Cloud and Security solutions.
• Support customers in improving security, compliance, and data protection.
• Troubleshoot technical issues and provide expert recommendations.
• Conduct product demonstrations, proof of concepts (PoC), and workshops.
• Work with Microsoft and other technology partners.
• Support project delivery and technical consulting activities.
• Create technical documentation and solution designs.
• What We're Looking For.
• 2+ years of experience in IT Infrastructure, Cloud, Security, or Microsoft Technologies.
• Good problem-solving and troubleshooting skills.
• Strong communication and customer-facing skills.
• Ability to work independently and take ownership of tasks.
• Passion for learning new technologies.
• Preferred Skills.
• Microsoft 365.
• Azure.
• Intune.
• Microsoft Defender.
• Microsoft Sentinel.
• Entra ID (Azure AD).
• Security & Compliance Solutions.
• Strong problem-solving skills.
• Good communication skills.
• Ownership mindset.
• Passion for technology and continuous learning.

ทักษะ:

Compliance, Research, Python

ประเภทงาน:

งานประจำ

• Build and Optimize Modern AI Applications: Design and deploy a range of LLM-powered solutions, including Retrieval-Augmented Generation (RAG) pipelines, natural-language data querying, tool-using and function-calling workflows, and other Generative AI applications, to deliver accurate, grounded, and citable responses..
• Develop Statistical and Machine Learning Models: Develop, deploy, and maintain traditional statistical models and machine learning algorithms (e.g., regression, classification, clustering) to solve structured data problems and complement broader AI ini ...
• Collaborate with the Data Team: Work together on data preprocessing, embedding generation, and pipeline integration, leveraging the AWS enterprise data platform to supply clean, well-governed data for AI workloads..
• Optimize and Harden Production Services: Improve production AI services for reliability, scalability, latency, and cost, document solutions clearly, and communicate outcomes to both technical and non-technical stakeholders..
• Monitor and Observe Production AI: Implement tracing, observability, and dashboards to track quality, latency, drift, and cost-per-task across the model lifecycle..
• Ensure AI Ethical Standards, Compliance, and Data Privacy: Apply input/output guardrails, PII redaction, access controls, and grounding safeguards, in alignment with internal data governance policies and emerging AI regulations..
• Mitigate AI-Assisted Development Risks: Critically evaluate and audit AI-generated code to prevent security vulnerabilities, logic flaws, and technical debt, ensuring deep technical understanding rather than over-reliance on automated code generation..
• Monitor and Observe Production AI: Implement tracing, observability, and dashboards to track quality, latency, drift, and cost-per-task across the model lifecycle..
• Ensure AI Ethical Standards, Compliance, and Data Privacy: Apply input/output guardrails, PII redaction, access controls, and grounding safeguards, in alignment with internal data governance policies and emerging AI regulations..
• Mitigate AI-Assisted Development Risks: Critically evaluate and audit AI-generated code to prevent security vulnerabilities, logic flaws, and technical debt, ensuring deep technical understanding rather than over-reliance on automated code generation..
• Bachelor s Degree or higher in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, or related technical field.
• 1 to 4 years of hands-on experience in AI/ML development, or an equivalent record of strong personal projects, research, or internships building applied AI/LLM solutions.
• Programming: Strong proficiency in Python for building AI/ML applications, including working with LLM APIs/SDKs and common AI libraries, as well as practical experience in data manipulation (e.g., using Pandas or SQL to clean and prepare data)..
• LLM Development: Hands-on experience building LLM-powered applications, including prompt design, tool/function calling, and connecting models to external data and tools..
• Retrieval & Vector Databases: Familiarity with vector databases, embedding models, and chunking/retrieval strategies (such as semantic chunking, hybrid search, and reranking)..
• Statistical Modeling & Machine Learning: Solid foundation in applied statistics, probability, and classical machine learning techniques. Proven ability to evaluate trade-offs and select the optimal modeling approach for specific business objectives..
• Cloud Computing: Experience with cloud platforms. AWS is the primary ecosystem for deploying and serving AI workloads, while familiarity with GCP or Azure is a welcome advantage..
• Engineering & LLMOps: Familiarity with version control (Git) and an awareness of general MLOps/LLMOps concepts (such as basic model testing, tracking performance, or managing prompts)..