> Markdown version of [/jobs/ext/3882545-backend-systems-engineer-agent-infrastructure](https://www.wearedevelopers.com/jobs/ext/3882545-backend-systems-engineer-agent-infrastructure). 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). --- # Backend / Systems Engineer, Agent Infrastructure - **Company:** Clera - **Location:** Berlin, Germany - **Experience:** Experienced - **Salary:** €80,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Software as a Service, Relational Databases, Python (Programming Language), PostgreSQL, Node.Js, TypeScript, Large Language Models, Backend, Fastapi - **Published:** October 23, 2026 - **Apply:** https://startup.jobs/backend-systems-engineer-agent-infrastructure-clera-10560476 ## About the Role * At least 3 years of backend engineering experience building and maintaining production services. * Practical experience with Python and/or TypeScript/Node.js, and willingness to work across both. * Experience with PostgreSQL or another relational database, including data modeling and transactions. * Experience with background jobs, queues, or event-driven processing, including failure handling and data consistency. * Strong backend fundamentals and experience designing reliable asynchronous workflows. * Experience with workflow engines, multi-tenant applications, authorization, FastAPI, or agent tooling is a plus. Prior LLM experience is not required. ## Description Build the backend systems and infrastructure that support reliable agent execution at an early-stage SaaS company. Working with the technical leadership and AI engineering team, you will own foundational architecture for persistent state, safe execution, permissions, and recovery., * Build backend services and data models to track operational work, ownership, and outcomes over time. * Develop asynchronous workflows that reliably handle retries, timeouts, external events, and interrupted execution. * Create shared APIs and tool-execution interfaces with authorization and customer-data isolation. * Improve how operational knowledge is stored, versioned, and served. * Strengthen testing and observability as the platform evolves. * Investigate production issues, design clear interfaces, and deliver maintainable solutions.