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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Ai Full-Stack Engineer - **Company:** Peak3 - **Location:** Madrid, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software as a Service, Cloud Engineering, Software Debugging, Distributed Systems, Python (Programming Language), PostgreSQL, Next.js, Software Safety, TypeScript, Workflow Management Systems, AI Infrastructure, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, AI Platforms, Kubernetes, Free and Open-Source Software, Machine Learning Operations, Front End Software Development, Serverless Computing - **Published:** September 27, 2026 - **Apply:** https://www.buscojobs.com.es/principal-ai-full-stack-engineer-en-madrid-ID-372722117 ## About the Role Proven track record shipping and operating production software at scale, ideally including an LLM/AI system taken from prototype to production. Fluent in Python or TypeScript and a modern frontend framework, with genuine comfort spanning backend, frontend, infrastructure, data, and model code. Hands-on LLM engineering depth: RAG/retrieval, function/tool calling, agent frameworks (LangGraph, LlamaIndex, or custom), systematic evals, prompt- and model-level optimization. Solid AI infrastructure grounding - vector databases, embedding models, model deployment/serving, inference optimization, distributed systems - with the operational discipline for regulated environments. Strong product instincts: can turn ambiguous problems into well-scoped solutions, cares about real user impact, and argues for simplicity when complexity isn't earned. High agency - prototypes and drives progress without waiting for complete specs. NicetoHave Taken an LLM system from 0 to 1 - prototype to real users, revenue, and operational load, including on-call and incident reviews. Agent infrastructure experience: secure execution sandboxes (gVisor, Firecracker, WASM), agent memory/state architectures, model routing, workflow orchestration. External technical signals - open-source contributions, technical writing, conference talks. Interest in multimodal AI, long-context engineering, applied AI safety/alignment, or RLHF. Finance or insurance domain experience (engineering ability and learning velocity matter more). Our stack: Python, TypeScript, React/Next.js, Postgres, Kubernetes, and various vector databases and LLM providers. xkdbapo Prior experience with every part isn't required - strong fundamentals and fast learning matter more. ## Description About Peak3Peak3 is an award-winning vertical SaaS provider, enabling more relevant, convenient, and affordable insurance protection for everyone through our technology and ingenuity.Together with our clients, we create a more resilient and innovative future.We combine insurance core, distribution, and AI solutions to deliver a step change in performance for insurers, MGAs, and insurance intermediaries.From greenfield embedded insurance ventures to multi-country core modernization programs, our SaaS solutions power top customers across life, health, and P&C insurance.Our 500+ colleagues are based across over 15 countries in Europe, Asia and the Middle East - with an ambitious roadmap to scale further.Lea el resumen de esta oportunidad para comprender qué habilidades, incluidas las habilidades interpersonales relevantes y el dominio de paquetes de software, se requieren.About The RoleAs a Principal AI Full-Stack Engineer on the AI Platform team, you'll own the design, build, and operation of the agentic AI systems powering our core insurance products - architecting LLM inference chains, building production AI infrastructure, shipping full-stack features from model to UI, and setting technical direction for the team.You should be as comfortable debugging a RAG recall failure in production as whiteboarding agent memory architectures with research or debating interaction patterns with design.ResponsibilitiesBuild agentic AI applications end-to-end - RAG pipelines, multi-agent orchestration, tool calling, workflows - and ship insurance agents that run in production.Design and optimize LLM inference chains: prompt engineering, structured outputs, fine-tuning (LoRA/PEFT), evals, and observability.Stand up production-grade AI infrastructure: vector databases, semantic retrieval, model gateways, inference acceleration, and cost governance.Own full-stack delivery - frontend (React/Next.js), backend (Python/TypeScript), cloud-native deployment (K8s/Serverless) - taking demos to policy volumes in the millions.Partner with actuarial, underwriting, and claims experts to turn domain knowledge into trustworthy, explainable, auditable AI systems.Experience & QualificationsProven track record shipping and operating production software at scale, ideally including an LLM/AI system taken from prototype to production.Fluent in Python or TypeScript and a modern frontend framework, with genuine comfort spanning backend, frontend, infrastructure, data, and model code.Hands-on LLM engineering depth: RAG/retrieval, function/tool calling, agent frameworks (LangGraph, LlamaIndex, or custom), systematic evals, prompt- and model-level optimization.Solid AI infrastructure grounding - vector databases, embedding models, model deployment/serving, inference optimization, distributed systems - with the operational discipline for regulated environments.Strong product instincts: can turn ambiguous problems into well-scoped solutions, cares about real user impact, and argues for simplicity when complexity isn't earned.High agency - prototypes and drives progress without waiting for complete specs.NicetoHaveTaken an LLM system from 0 to 1 - prototype to real users, revenue, and operational load, including on-call and incident reviews.Agent infrastructure experience: secure execution sandboxes (gVisor, Firecracker, WASM), agent memory/state architectures, model routing, workflow orchestration.External technical signals - open-source contributions, technical writing, conference talks.Interest in multimodal AI, long-context engineering, applied AI safety/alignment, or RLHF.Finance or insurance domain experience (engineering ability and learning velocity matter more).Our stack: Python, TypeScript, React/Next.js, Postgres, Kubernetes, and various vector databases and LLM providers.xkdbapo Prior experience with every part isn't required - strong fundamentals and fast learning matter more.