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# (Senior) Backend Engineer

- **Company:** Legalhero GmbH
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Data Infrastructure, Relational Databases, Distributed Systems, Java Virtual Machine (JVM), MySQL, Management of Software Versions, Large Language Models, Backend, Kotlin, Kubernetes, Front End Software Development
- **Published:** May 22, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=3ae8c94efbe4a27a

## About the Role

Do you have experience in MySQL?, Do you have a Master's degree?, * 6+ years in backend engineering, including 2+ years at senior level

 * Strong proficiency in Kotlin or Java - JVM idioms feel like home
 * Relational databases (MySQL or similar) and at least one public cloud in production, AWS preferred
 * Distributed systems thinking as a reflex: idempotency, retries, eventual consistency, observability
 * Business fluent English; German at B1 or a clear commitment to get there within 12 months

Nice to have - and what you'll pick up here:

 * Micronaut, Kubernetes, AWS Bedrock, LiteLLM, the official Claude Agent SDK, MCP-based architecture
 * Experience with regulated data environments (GDPR, BaFin, §203 StGB)

## Description

Backend engineering at Legal Hero means full ownership. You'll design and run services in our Kotlin/Java stack with Micronaut on AWS, wire LLM capabilities reliably into product flows, harden production systems, and actively shape our testing, deployment, and observability practice - together with a team that takes the craft seriously.

 * Design and own scalable backend services from first commit to production - APIs, data models, versioning, SLOs, and on-call included
 * Build and evolve high-performance, secure infrastructure that handles real load - not just greenfield, but messy reality
 * Wire LLM-powered capabilities reliably into product flows: suggestion APIs, RAG-backed endpoints, agent tool calls - you make AI actually land in production
 * Work closely with frontend, product, and AI teams - your APIs are their foundation, so you design them to last
 * Make the hard tradeoffs: schema migrations, breaking changes, dependency upgrades - with judgment, not just best practices
 * Raise the quality bar through automated testing (unit, integration, end-to-end) and push for architectural improvements that matter
 * Lead incident investigations on your own services, write the postmortem, and escalate only once you have answers


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