Technical Leadership & Architecture

• Own the architecture of agentic AI systems: orchestration, retrieval, evaluation, observability, and scaling.
• Drive system design for complex, multi-service, multi-agent platforms — making and justifying high-impact trade-offs.
• Define technical standards, patterns, and best practices for Python services, agentic workflows, and data pipelines.
• Lead build-vs-buy and framework/vendor decisions across LLM providers, vector stores, and agent frameworks.
• Anticipate scaling, cost, latency, reliability, and safety challenges before they become incidents.

Agentic AI at Scale

• Architect production agentic workflows with OpenAI Agents SDK (preferred) and durable orchestration via Temporal.
• Design agents where MCP, tool use, and RAG pipelines are central; own the retrieval, vector store, and embeddings strategy.
• Champion an evals-first approach — set the standard that agents are designed, built, and gated on measurable evals, with regression gating in CI.
• Use whichever LLM/multimodal provider best fits the problem at hand.

Hands-On Engineering

• Personally design and ship the hardest parts of the system in Python (primary) and TypeScript/JavaScript.
• Set the standard for clean, production-grade, well-tested, observable code.
• Strong with SQL for analytics powering retrieval, evaluation, and reporting.

Full-Stack & Platform

• Frontend: React. Backend: GraphQL, MCP, and REST APIs.
• Establish CI/CD, Docker, Kubernetes, and observability practices for the team.

Mentorship & Influence

• Mentor Dev II/III engineers; lead design reviews and resolve ambiguity across teams.
• Communicate technical strategy clearly to engineering leadership, product, and non-technical stakeholders.

• 8+ years in Software Engineering (or Data Science with deep engineering), with substantial hands-on Generative AI / agentic experience and shipped production systems.
• A strong systems thinker, designer, and architect who sets technical direction and drives solutions independently.
• Demonstrated technical leadership — setting architecture, driving decisions, and mentoring engineers.
• Languages: Python (expert), SQL (good for analytics), TypeScript/JavaScript.
• Agentic stack: OpenAI Agents SDK (preferred), Temporal workflows; LangSmith for building/eval (good to have).
• Backend / Frontend: GraphQL, MCP, REST APIs; React.
• Cloud: GCP (Kubernetes / GKE) and AWS (ECS, EC2); Docker and CI/CD.
• Observability: ELK, LangSmith, OpenAI tracing.
• Evals-first as a core engineering discipline.

Nice to Have

• RAG / ML knowledge and MLOps.
• Voice / realtime agents: VAD, latency optimization, STT/TTS.
• Prior experience as a tech lead, staff engineer, or architect.