AI Engineer
sparrowrms
Job Description
- Design, build, and iterate LLM-powered workflows — retrieval, routing, tool use, function calling, multi-step agents.
- Implement agentic apps that plan, call tools/APIs, and maintain state across tasks.
- Build RAG pipelines end-to-end: ingestion, chunking, embeddings, indexing, and latency-optimized retrieval — including layout-aware parsing of drawings and reports.
- Own prompt engineering and evaluation: golden datasets built with domain experts, A/B tests, guardrails, and metrics across latency, cost, quality, and safety.
- Productionize with observability (traces, tokens, failures), cost controls, and fallbacks (LangSmith / Langfuse / Arize or equivalent).
- Ship backend services and APIs (Python / FastAPI) integrating with data stores, vector DBs, and time-series sources.
- Handle deployment reality for industrial clients: VPC, on-prem, or air-gapped environments and self-hosted open models where data can't leave the plant.
- Collaborate with PM/Design and SMEs to translate requirements into reliable, safe, user-facing features.