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AI Integration Engineer
Put language models where they earn their place — screening, classification, intelligence, drafting — grounded in our own data, with the evaluation discipline to keep them honest.
What you'll do
- Build agent features on the Anthropic SDK with structured, typed outputs.
- Engineer retrieval (Qdrant + Voyage) so outputs are grounded and cited, not generic.
- Treat prompts as code: versioned, tested, evaluated; defend against prompt injection.
- Keep cost, latency, and a human approval gate firmly in view.
What we're looking for
- Strong engineering in Go or TypeScript.
- Hands-on with LLM APIs and RAG / embeddings in something real.
- An evaluation mindset — you measure model output, you don’t trust vibes.
Nice to have
- Go
- Vector databases
- Safety / prompt-injection experience
- Data plumbing
What success looks like in 90 days
- Shipped a grounded, evaluated agent feature.
- Stood up a small eval harness others use.
- Cut a cost or quality problem with data, not guesswork.
Stack
GoTypeScriptAnthropic SDKQdrantVoyage
The process
01
Apply
CV + cover letter
02
Screen
we read every one
03
Assessment
a real, scoped task
04
Interview
the team you’d join
05
Founder talk
values & direction
06
Offer
terms discussed openly
07
Onboard
paired, shipping in week one
Apply for this role
You're applying for AI Integration Engineer.
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