Job Opportunities API

The AI Engineer builds production agents end-to-end on an AI-native retail decisioning platform — prompt design, tool definitions, multi-step workflows on the agent runtime (LangGraph, CrewAI, or chosen framework), evaluation harnesses (golden sets, regression gates, multi-step replay), human-in-the-loop gate integration, and per-agent cost optimisation. The role consumes platform-provided LLM and vector services; it does not rebuild that platform.  Remote candidates outside of Thailand are welcome to apply. Key Responsibilities: Build agents on the platform's agent runtime — prompt design, tool definitions, multi-step workflows, error handling — and ship them with eval harness, human-in-the-loop gate config, observability instrumentation, cost meter, and runbook.  Co-design agent specs with Tech Lead Applications and Suite Product Owners; partner with ML Engineers on classical ML model integration into agents.  Author golden sets per agent — domain-specific test cases capturing must-pass behaviours; build regression gates in CI so no agent ships without eval-pass.  Implement multi-step conversation replay for agents with stateful interactions; use LLM-as-judge patterns where appropriate; instrument human feedback collection.  Configure HITL gates per agent and per agent plan; implement gate-progression evidence collection (Shadow data, accuracy metrics, override frequency).  Own per-agent cost meter — tokens, vector queries, model inference; report monthly; tune model routing and implement caching strategies where appropriate.  Consume the enterprise LLM Gateway via standard SDK; partner with platform AI engineering on embedding model selection and retrieval relevance tuning.  Mentor seed-programme engineers and contribute to the agent-engineering playbook.  Requirements Bachelor's or Master's degree in Computer Science, AI / ML, or a related discipline.  5+ years software engineering with 2+ years shipping LLM-based or agentic systems to production.  Production agent or multi-step LLM workflow experience — LangGraph, CrewAI, AutoGen, DSPy, or custom.  Strong Python; comfortable with async, observability, testing.  Hands-on with at least one major LLM provider (Azure OpenAI, Anthropic, Bedrock, Vertex).  Eval-driven LLM development — golden sets, LLM-as-judge, regression gates, multi-step replay.  HITL gate / agent governance — has shipped agents with explicit gates, not autonomous-by-default.  Prompt injection / data leakage / PII handling — designs and tests defences.  Preferred Qualifications Open-source contributions to agent frameworks (LangChain / LangGraph / DSPy).  Multi-agent system at scale in production; retail / commerce / fintech agentic workflows (supplier onboarding, contract intelligence, comparable).  Causal inference exposure (DoWhy / EconML); Thai-language NLP (PyThaiNLP, WangchanBERTa, SEA-LION, Typhoon).  Vendor certifications such as Databricks Generative AI Engineer or Azure AI Engineer Associate.