AI Engineer

Join to apply for the AI Engineer role at Quadrivia AI Own and evolve the core "brain" service that powers Qu. Design, build, and operate multi-agent LLM systems that communicate in real time over text and voice. Ship fast Python services with FastAPI, keep latency low, quality high, and evaluation continuous. What You'll Do * Own Qu's brain service end to end: architecture, SLAs, latency budgets, error modes, rollouts. * Low-latency comms: streaming text and voice, VAD, barge-in, turn-taking, interruption handling. WebRTC, SIP, and LiveKit experience is a strong plus. * Multi-agent orchestration: planner-executor-critic patterns, role routing, shared memory, tool routers, coordination protocols and evaluation. * Reasoning & optimization: ReAct, Chain-of-Thought, plus Tree-/Graph-of-Thoughts when useful. * Programmatic prompt optimization: DSPy for prompt/program compilation; integrate MiPRO and GEPA for iterative prompt evolution under eval constraints. * RAG engineering: high-signal retrieval (chunking, hybrid search, re-ranking), query rewriting, compression, caching, freshness, and strong grounding; evaluate faithfulness, context precision/recall, and answer relevancy. * Evaluation & observability: Pre-call validate inputs, enforce safety, and verify retrieval quality for RAG; in-call trace prompts, tool calls, token/latency/cost and enforce streaming guardrails; post-call run automated task evals (faithfulness, relevancy, hallucination, safety), regressions, red-teaming, and CI/CD gates. Instrument with structured logs and OpenTelemetry, surface dashboards and alerts, and feed live traffic slices into shadow evals for drift detection. Minimum Qualifications * 5+ years in ML or backend engineering in product environments; recent focus on LLM systems. * Expert Python. Strong FastAPI, asyncio, pydantic, and production observability. * Real-time systems: you've built or integrated low-latency text/voice. You have used LiveKit, Pipecat or similar tech.

• Working knowledge of agent patterns and eval-driven development. * Hands-on with ReAct and CoT; pragmatic with ToT/GoT tradeoffs. * Prior startup experience. Nice To Have * DSPy for compilation and self-improving workflows; MiPRO/GEPA integration. * Experience with evaluation tooling and LLM-as-judge setups. * WebRTC/SRTP, jitter buffers, SIP basics; LiveKit a plus. Example Problems You'll Tackle * Push median voice round-trip under 2 seconds while preserving turn-taking and barge-in. * Set up OTEL-first tracing for the agent graph with automated eval triggers on production traffic slices. * Improve our RAG pipeline with hybrid retrieval and re-ranking, then prove gains via faithfulness and context metrics with regression harnesses. * Turn EHR integrations into LLM tools. What You Get * Work on cutting-edge real-time agent tech with a best-in-class team healthtech. * Fun off-sites in Barcelona. * High-tech laptop and solid dev ergonomics. * Flexibility: work from home or