Careers
AI Engineers
You build the retrieval, pipelines, serving, and evals that power thousands of agents reasoning over a 20-year, ~200,000-business data lake — and you make it fast, cheap, and reliable.
Build the AI infrastructure behind Hydra OS.
What you'll do
- ✓Design RAG/CAG end to end: chunking strategy, embedding models, hybrid (vector + keyword) search, reranking, and freshness/invalidation.
- ✓Own the data lake and ingestion pipelines — schema, dedup, backfills, and incremental updates feeding retrieval.
- ✓Drive down LLM cost and latency: model routing, prompt/response caching, batching, streaming, and per-task token budgets.
- ✓Stand up offline eval sets and online quality metrics, with tracing and alerting on regressions.
- ✓Expose clean, typed inference and retrieval services that other engineers and agents build on.
- ✓Run capacity, rate-limit, and fallback strategy across multiple model providers.
You're probably a fit if
- You understand AI infrastructure at scale — retrieval, serving, caching, and observability.
- You're heavy on the back office: pipelines, vector stores, queues, and SLOs.
- You've tuned a RAG system and can explain why recall or precision moved.
- You track cost-per-task and p95 latency, and you hate guessing.
- You've operated production data/ML systems, not just run notebooks.
The stack
- Vector DBs: pgvector / Pinecone / Qdrant
- Embeddings, rerankers, hybrid search
- Python + data pipelines
- Redis / caching, model routing
- Eval + tracing tooling, SLOs
What we expect before you apply
- 3+ years in backend, ML, or data infrastructure with a production retrieval or LLM-serving system you've owned.
- Fluency treating cost, latency, and reliability as measurable, first-class metrics.
- A public GitHub showing infra-grade work you've shipped.
The bar, for every role
- Builders, not talkers. You ship products on your own. Your GitHub proves it.
- Dev background first. You earned vibe coding the hard way — real development experience before AI-assisted coding.
- Obsessed with the craft. You can't sleep till it's done, and your feed is constantly full of learning.
- AI infrastructure at scale. A solid understanding is a strong plus — heavy on the back office, or elite at UI/UX.
- A marketing brain. Bonus points if you've built AI automation systems for paid advertising.
- Client-fluent. You work hand-in-hand with non-technical clients — idea to prototype to production, then sell and get results.
- Forward-looking. You see where the world is going, not just where it's been.
- Thrives in fast water. You're built for a fast-changing, ever-evolving environment. So are we.