About the role
Requirements:
- 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.
Background That Maps Well:
- 3+ 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.