About the role
Responsibilities:
- Production builder: You've shipped LLM-powered features real users depend on and debugged them when they broke.
- LLM practitioner: You understand hallucinations, retrieval failures, context limits, and what it takes to make agents deterministic enough for enterprise use.
- Systems thinker: You design for latency, failure modes, retry logic, and observability before features.
- Enterprise-aware: Data residency, compliance, audit trails, and deterministic guardrails are first-class design constraints for you.
Requirements:
- 10+ years in AI/ML or backend engineering with strong AI exposure.
- Hands-on production experience with LLM APIs (Anthropic, OpenAI, Cohere).
- Experience designing evaluation frameworks: automated evals, regression tests, or LLM-as-judge pipelines.
- Strong Python; experience with LangChain, LlamaIndex, or similar agentic frameworks.
- Familiarity with RAG architectures: chunking, embedding models, vector DBs, retrieval quality.