AI Engineer

ReadMeDeveloper Tools

Remote, USFull-TimeMiddle

Salary not disclosed

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Job Details

Experience building with LLMs in production.
Strong JavaScript/TypeScript experience.
Strong Python experience.
Experience with Embeddings and retrieval systems (RAG).
Experience with Prompting and structured outputs.
Experience with Evaluation and iteration of AI systems (quality, latency, cost).
Comfort working with APIs and structured data (JSON, OpenAPI, schemas).
Experience designing and shipping end-to-end systems, from backend pipelines to user-facing product surfaces.
Strong instincts around when to use AI vs. deterministic approaches.
Experience improving AI reliability, observability, and production readiness.
Familiarity with real-world edge cases (messy data, inconsistent inputs, ambiguous queries) and how to handle them.

Help decide what gets built, why it matters, and how it works end-to-end.
Work on systems that are already live across thousands of developer hubs and define what they become next.
Design end-to-end AI systems combining LLMs, embeddings, retrieval pipelines, and structured outputs into reliable product features.
Build grounding and retrieval layers: indexing docs, OpenAPI specs, and customer data to support accurate, context-aware generation.
Define evaluation systems: measuring accuracy, latency, cost, and user impact; building feedback loops to continuously improve quality.
Handle real-world complexity: malformed specs, inconsistent docs, edge-case APIs, and ambiguous user queries.
Make architectural tradeoffs: latency vs. quality, cost vs. coverage, deterministic vs. generative approaches.
Own production reliability: observability, fallbacks, rate limiting, and safe degradation when systems fail.
Work across the stack: from model orchestration and backend systems to the UI surfaces that expose them.

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