AI Engineer
Function: AI Engineering / Applied AI Delivery
About the Role
We're hiring an AI Engineer to design, build, and ship production AI systems — not prototypes, not notebooks. This is a builder's role: you'll own the path from "we think an LLM/agent could solve this" to a system running reliably in production, under real load, with real failure modes.
We are being deliberately selective here. This role is not for someone who has "used ChatGPT a lot" or built a weekend RAG demo. We want people who have shipped agentic or LLM-powered systems that other engineers depend on, who understand why those systems break, and who can hold their own in a room full of skeptical senior engineers. If that's not you yet, this probably isn't the right role yet either — and that's fine.
Requirements
What You'll Own
- Design and build production-grade AI/agentic systems — from architecture through deployment, monitoring, and iteration — not just model calls wrapped in a script
- Own the full lifecycle of at least one non-trivial AI capability: problem framing, evaluation strategy, prompt/context engineering, orchestration, deployment, and post-launch tuning
- Build deterministic guardrails around probabilistic components — retries, validation, fallback paths, human-in-the-loop checkpoints where confidence is low
- Design evaluation harnesses and offline/online eval pipelines that actually catch
