> Markdown version of [/jobs/ext/2176428-ai-platform-engineer](https://www.wearedevelopers.com/jobs/ext/2176428-ai-platform-engineer). 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 Platform Engineer - **Company:** Peak3 (Formerly Za Tech) - **Location:** Coslada, Spain - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software as a Service, Cloud Engineering, Distributed Systems, Python (Programming Language), PostgreSQL, Next.js, Secure Coding, TypeScript, Datadog, Data Logging, ReactJS, Large Language Models, Multi-Agent Systems, Caching, Backend, AI Platforms, Kubernetes, Machine Learning Operations, Serverless Computing - **Published:** August 22, 2026 - **Apply:** https://www.buscojobs.com.es/ai-platform-engineer-en-coslada-ID-368234953 ## About the Role Solid experience in Python or TypeScript, with working knowledge of backend infrastructure and cloud-native deployment (K8s or serverless). Hands-on experience with vector databases, embedding models, and model deployment/serving patterns. Some experience with LLM inference optimization, caching, and observability tooling. Familiarity with RAG pipelines, function/tool calling, or agent frameworks (LangGraph, LlamaIndex, or similar) - deep expertise not required, willingness to grow into it is. Comfortable operating in production environments and taking ownership of reliability and performance. High agency and a builder mindset - willing to dig into infra problems without waiting for complete specs. Nice to Have Experience with secure code execution sandboxes (gVisor, Firecracker, WASM) or long-running workflow orchestration. Exposure to model routing across providers or agent memory/state architectures. Interest in distributed systems, cost governance, or FinOps for AI workloads. Finance or insurance domain experience (not required - engineering fundamentals and learning velocity matter more). Our stack: Python, TypeScript, React/Next.js, Postgres, Kubernetes, and various vector databases and LLM providers. xqysrnh Prior experience with every part isn't required - strong fundamentals and fast learning matter more. ## Description About Peak3Dé el siguiente paso en su carrera profesional ahora: desplácese hacia abajo para leer la descripción completa del puesto y envíe su solicitud.Peak3 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.About the RoleAs an AI Platform Engineer on the AI Platform team, you'll build and operate the infrastructure that keeps our agentic AI systems fast, reliable, and cost-effective in production.Working closely with our Principal AI Full-Stack Engineer, you'll take architectural direction and turn it into solid, well-monitored infrastructure - vector databases, model gateways, inference pipelines - that the rest of the team builds on.ResponsibilitiesBuild and maintain core AI infrastructure: vector databases, semantic retrieval, model gateways, and inference pipelines.Implement inference optimization and caching to keep latency and cost within target.Set up and maintain observability for LLM systems - logging, tracing, evals monitoring, cost tracking.Support production incidents and on-call for AI systems, including runbooks and postmortems.Work with the Principal AI Full-Stack Engineer to implement architecture decisions and contribute to full-stack features when needed.Experience & QualificationsSolid experience in Python or TypeScript, with working knowledge of backend infrastructure and cloud-native deployment (K8s or serverless).Hands-on experience with vector databases, embedding models, and model deployment/serving patterns.Some experience with LLM inference optimization, caching, and observability tooling.Familiarity with RAG pipelines, function/tool calling, or agent frameworks (LangGraph, LlamaIndex, or similar) - deep expertise not required, willingness to grow into it is.Comfortable operating in production environments and taking ownership of reliability and performance.High agency and a builder mindset - willing to dig into infra problems without waiting for complete specs.Nice to HaveExperience with secure code execution sandboxes (gVisor, Firecracker, WASM) or long-running workflow orchestration.Exposure to model routing across providers or agent memory/state architectures.Interest in distributed systems, cost governance, or FinOps for AI workloads.Finance or insurance domain experience (not required - engineering fundamentals and learning velocity matter more).Our stack: Python, TypeScript, React/Next.js, Postgres, Kubernetes, and various vector databases and LLM providers.xqysrnh Prior experience with every part isn't required - strong fundamentals and fast learning matter more. ## Related Videos - [Watch Tests Go Brrrr! 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