āđāļāļāđāļē āļ§āđāļēāļ§ āļāļģāļāļąāļ
QA Automation Engineer (Senior)
āļāļĩāđāđāļāļāđāļē āļ§āđāļēāļ§ āļāļģāļāļąāļ- 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 not there.
- 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.
- 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.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļĩāđāļāļģāđāļāđāļ
- 4 āļāļĩ
āļĢāļ°āļāļąāļāļāļģāđāļŦāļāđāļāļāļēāļ
- āļĢāļ°āļāļąāļāļāļđāđāļāļąāļāļāļēāļĢ / āļāļēāļ§āļļāđāļŠ
āđāļāļīāļāđāļāļ·āļāļ
- 64,210 - 89,180 THB, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
āļŠāļēāļĒāļāļēāļ
- āļ§āļīāļĻāļ§āļāļĢāļĢāļĄ
āļāļĢāļ°āđāļ āļāļāļēāļ
- āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļīāļĐāļąāļ
āļāļģāļāļ§āļāļāļāļąāļāļāļēāļ:10-50 āļāļ
āļāļĢāļ°āđāļ āļāļāļĢāļīāļĐāļąāļ:āđāļāļāđāļāđāļĨāļĒāļĩāļŠāļēāļĢāļŠāļāđāļāļĻ
āļāļĩāđāļāļąāđāļāļāļĢāļīāļĐāļąāļ:āļāļĢāļļāļāđāļāļ
āđāļ§āđāļāđāļāļāđ:www.facebook.com/datawowio/
āļāđāļāļāļąāđāļāđāļĄāļ·āđāļāļāļĩ:2013
Data Wow āđāļāđāļāļāļĢāļīāļĐāļąāļāļāļĩāđāļāļĢāļķāļāļĐāļēāļāđāļēāļāļāđāļāļĄāļđāļĨāđāļĨāļ° AI āļŠāļąāļāļāļēāļāļīāđāļāļĒ āļāđāļāļāļąāđāļāđāļāļāļĩ 2019 āđāļŦāđāļāļĢāļīāļāļēāļĢāļāđāļēāļāļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļāđāļāļĄāļđāļĨ (Data Engineering) āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨ āļāļēāļĢāļāļąāļāļāļēāđāļĄāđāļāļĨ AI āđāļĨāļ° Machine Learning āļāļēāļĢāļāļīāļāļāđāļēāļĒāļāđāļāļĄāļđāļĨ (Data Labeling) āđāļĨāļ°āļāļēāļĢāļŠāļĢāđāļēāļāđāļāļĨāļāļāļāļĢāđāļĄāļāđāļāļĄāļđāļĨāđāļŦāđāļāļąāļāļāļāļāđāļāļĢāļāļąāđāļāļāļģāđāļāļāļĢāļ°āđāļāļĻāđāļāļĒāđāļĨāļ°āļāļĩāđāļāļļāđāļ
āļĢāđāļ§āļĄāļāļēāļāļāļąāļāđāļĢāļē: Data Wow is a Thai data and AI consultancy where engineers and data scientists ship real products for enterprise clients.
āļāđāļēāļāļāđāļ
āđāļāļāļāļĩāđāļāļąāđāļāļāļĩāđāļāļģāļāļēāļ: āļāļāļļāļĄāļ§āļąāļ
āļŠāļģāļāļąāļāļāļēāļāđāļŦāļāđ: 1778 Summer Hub Office 6th Floor, Sukhumvit Rd, Phra Khanong, Khlong Toei, Bangkok 10110
āļŠāļ§āļąāļŠāļāļīāļāļēāļĢ
- āļāļāļĢāđāļŠāđāļĢāļĩāļĒāļāļ āļēāļĐāļēāļāļąāļāļāļĪāļĐ
- āļāđāļēāđāļāļīāļāļāļēāļ
- āļāļąāđāļ§āđāļĄāļāļāļģāļāļēāļāļĒāļ·āļāļŦāļĒāļļāđāļ
- āļāļģāļāļēāļ 5 āļ§āļąāļ/āļŠāļąāļāļāļēāļŦāđ
- āļāļĢāļ°āļāļąāļāļŠāļļāļāļ āļēāļ
- āļāļĢāļ°āļāļąāļāļŠāļąāļāļāļĄ
- āđāļāļāļēāļŠāđāļāļāļēāļĢāđāļĢāļĩāļĒāļāļĢāļđāđāđāļĨāļ°āļāļąāļāļāļē
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āļāļģāđāļŦāļāđāļāļāļēāļāļ§āđāļēāļāļāļĩāđāļāļļāļāļāđāļēāļāļ°āļŠāļāđāļ
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