Job Opportunities API

The Tech Lead — AI Platform is the senior technical leader for the platform runtime, AI engine, and agent-orchestration tier of an AI-native retail decisioning platform. The role is accountable for architectural integrity, build vs buy decisions, integration with upstream data and knowledge-graph services, and the agent runtime's safety and scale properties — and leads a team of senior software, AI, and ML engineers.  Remote candidates outside of Thailand are welcome to apply. Key Responsibilities: Own the reference architecture for the platform's runtime, decisioning, and agent-execution tiers; co-chair the Architecture Review Board; author Architecture Decision Records.  Design, build, and operate the agent runtime (LangGraph, CrewAI, or chosen framework) — deployment, scale, observability, cost per invocation.  Design and ship an agent autonomy framework with progressive trust levels (shadow / recommender / executor patterns) and measurable gate criteria; operationalise human-in-the-loop patterns for every agent.  Own the agent registry — catalogued, versioned, owned, gated, monitored agents.  Define and operationalise the consumption contract with upstream knowledge-graph, semantic-layer, data-product, and event-stream services from the platform team.  Lead the AI-side decisioning components — orchestrator, trust gate service, agent-side helpers — and coordinate consumption of LLM Gateway and Vector Search services.  Lead a team of senior software, AI, and ML engineers; mentor on agent-engineering discipline; partner with peer Tech Leads on handoffs into application and experience layers.  Own runtime SLOs — invocation P95, success rate, HITL response time — and per-agent cost meter; lead incident response for runtime degradation.  Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.  8+ years software engineering with 3+ years in a Tech Lead / Staff role owning platform standards.  Production agentic systems experience — multi-agent orchestration, HITL gates, eval-driven CI; not just RAG demos.  Strong distributed-systems fundamentals — concurrency, message queues, observability, performance.  LLM platform depth — at least one major provider (Azure OpenAI, Anthropic, Bedrock, Vertex) in production with cost / latency optimisation.  API-first design discipline — service contracts, SLOs, versioning, deprecation policies.  Cloud platform experience (Azure preferred; AWS / GCP transferable).  Architectural authorship — has written ADRs, chaired ARB, made build-vs-buy calls with executive sponsors.  Preferred Qualifications: Built or led a production multi-agent platform serving multiple business consumers.  Open-source agent framework contributions (LangChain / LangGraph / AutoGen / DSPy).  Retail / commerce / fintech domain experience; knowledge-graph production experience (Neo4j, Neptune, TigerGraph).  Causal inference exposure (DoWhy / EconML).