> Markdown version of [/jobs/ext/1414383-ai-engineer-backend](https://www.wearedevelopers.com/jobs/ext/1414383-ai-engineer-backend). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer Backend - **Company:** Quadrivia Ai - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, ARM Architecture, Cloud Computing, Data Stores, Python (Programming Language), PostgreSQL, Automation of Marketing, Redis, Software Engineering, WebRTC, Data Logging, Large Language Models, Multi-Agent Systems, Backend, Fastapi, Api Design, Domain Driven Design, Docker - **Published:** July 24, 2026 - **Apply:** https://www.jobleads.com/es/job/e26b2327dc56cc41e02cb3d9a2b169f98 ## About the Role * Your core is backend and software engineering. You write clean, maintainable services and you care how they behave in production. * Deep understanding of architectural design patterns (e.g., Clean/Hexagonal Architecture, Domain-Driven Design, SOLID, event-driven) to manage complex system boundaries. * At least 2 years, demonstrable, building or scaling user-facing AI software that real users touched. We'll want to see it. * Expert Python, with strong FastAPI, asyncio, pydantic, and production observability. * Comfortable with agent patterns and eval-driven development. * You've worked at a startup before and know what wearing several hats actually costs. ## Description You'll build and run Cortex, the core AI architecture behind Q, and the services that sit on top of it: automated AI audits, patient simulators, retrieval (RAG), and the escalation agents that take over in red-guardrail situations. This is a backend role first. The job is to make our AI systems reliable, fast, and observable in production, not to invent new ML. You own the software underneath the agents., * Design and maintain robust, modular backend systems using clean architectural (SOLID) principles to ensure long-term maintainability, scalability and flexibility as the agentic stack evolves. * Own Cortex end-to-end: architecture, API design, service boundaries, reliability targets, and proactively managing failure modes. * Build the platform services around it: the automated audit and eval pipeline, patient simulators for testing agents at scale, and the retrieval layer. * Write fast, well-tested Python services with FastAPI, asyncio, and pydantic, and get the queues, caching, and data stores right. * Wire up the multi-agent orchestration: routing between agents, shared state, and clean tool interfaces. * Engineer the RAG pipeline for high-signal retrieval (chunking, hybrid search, re-ranking, caching) and prove the grounding holds. * Make the whole thing observable: structured logs, OTEL tracing across the agent graph, cost, latency and token visibility, dashboards, and CI gates that catch regressions before they ship., * Real-time and voice: WebRTC, LiveKit, SIP, VAD, barge-in, turn-taking. Useful here, not required. * Programmatic prompt optimization techniques. * LLM-as-judge setups and other evaluation tooling. * GCP: Cloud Run or GKE, Pub/Sub, Vertex AI, GCS, Secret Manager, Cloud Logging and Trace. * Healthcare data familiarity. Example Problems You'll Tackle * Stand up the AI audit pipeline so evals run automatically on slices of production traffic, with regression gates wired into CI. * Build a patient simulator that lets us stress-test agents at scale before they ever reach a real call. * Improve the RAG pipeline with hybrid retrieval and re-ranking, then prove the gains with faithfulness and context metrics. * Get OTEL-first tracing across the agent graph, with automated eval triggers on live traffic. * Turn EHR integrations into reliable tools the agents can call. ## Related Videos - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Transforming Education: A Journey from interactive Markdown to Remote-Labs](https://www.wearedevelopers.com/videos/941-transforming-education-a-journey-from-interactive-markdown-to-remote-labs) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [AX is the only Experience that Matters](https://www.wearedevelopers.com/videos/1404-ax-is-the-only-experience-that-matters) - [Hello JARVIS - Building Voice Interfaces for Your LLMS](https://www.wearedevelopers.com/videos/1641-hello-jarvis-building-voice-interfaces-for-your-llms) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)