Key Responsibilities

• Design, build, and optimize LLM pipelines including retrieval, context assembly, grounding, prompting, and tool-calling.
• Develop RAG systems using vector databases, metadata design, chunking strategies, and hybrid retrieval approaches.
• Build agentic workflows and function-calling systems capable of reasoning, planning, and executing tasks.
• Evaluate model performance using structured test suites, synthetic QA generation, and benchmark datasets.
• Work closely with product and domain experts to translate ambiguous requirements into clear, structured LLM tasks.
• Diagnose and mitigate failure modes such as hallucinations, retrieval misses, and context collisions.
• Apply lightweight fine-tuning or LoRA when needed for task-specific improvements.
• Develop and maintain backend components for LLM pipelines (FastAPI, event systems, queues).
• Prepare unstructured documents (PDFs, HTML, logs, knowledge bases) for ingestion and indexing in vector/RAG systems.
• Support deployment across cloud or on-prem infrastructure (vLLM, TGI, Ollama, GPUs, token-budgeting).
• Ensure all AI features are grounded, safe, testable, reproducible, versioned, and backed by real evaluation—not guesswork.

Requirements

Required

• Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, Statistics, or related field; or equivalent practical experience.
• 1–3 years of experience in a data / AI / analytics / software role, or strong project portfolio demonstrating equivalent capability (strong fresh graduates will be considered if portfolio is solid).
• Practical proficiency in Python for:
• Data handling (e.g. pandas, basic NumPy)
• Calling APIs and working with JSON
• Writing small scripts/services
• Practical proficiency in SQL (e.g. MySQL, PostgreSQL) for querying, joining, and aggregating data.
• Experience with at least one BI / dashboarding tool (Looker Studio, Metabase, Power BI, Tableau, or similar).
• Hands-on experience using LLM / AI APIs in projects (personal, academic, or production), not only theoretical knowledge.
• Ability to structure problems, work independently on tasks, and deliver within agreed timelines.
• Ability to communicate clearly in Thai, with working proficiency in English for tools, documentation, and some communication.

Benefits

• Health Insurance
• Hybrid
• Annual Leave 12 days
• Mental Health counseling sessions with psychiatrists and psychologists through ooca platform
• Social Security Insurance
• Provident Fund (condition applied)
• Annual Health check-up (condition applied)
• Special discount home loan interest with Government Housing Bank
• BYOD policy: Personal laptops less than 3 years old are eligible for 1000 THB/month subsidy (registration required)