ABOUT THE OPPORTUNITY

Join an international technology company building a sophisticated, high-performance platform used worldwide in business aviation. Work in a collaborative engineering team with meaningful ownership and an emphasis on code quality, modern backend practices and pragmatic AI adoption. This is a hands-on software engineering role, not an AI research or architecture-only position.

PROJECT & CONTEXT

Develop and improve a large Java backend powering web applications, mobile experiences and integrations with external systems. Implement reliable features end-to-end, working closely with product and engineering colleagues. The environment includes distributed services, asynchronous event processing and AI-assisted development. We are particularly interested in engineers who understand agentic LLM workflows and can apply that knowledge in practical Java development, including integrations, retrieval and automation where relevant.

WHAT WE'RE LOOKING FOR (Required)

• 6+ years of hands-on Java backend engineering, ideally Java 17, with Spring Boot (2.x/3.x) and Hibernate (5.x/6.x).
• Experience building and maintaining scalable distributed systems, REST APIs and relational data models with PostgreSQL.
• Practical event-driven development with Apache Kafka or comparable messaging/streaming technologies.
• Strong familiarity with functional programming principles, including immutability, pure functions and concurrency-aware design.
• Hands-on familiarity with LLMs and agentic workflows, including RAG pipelines, agent/tool interactions and LLM orchestration; ability to discuss concrete implementations.
• Regular use of AI-assisted coding tools such as Cursor, Claude Code or GitHub Copilot, with sound judgment about code quality and testing.
• Git, Maven, testing, debugging and end-to-end delivery ownership.
• Strong collaboration skills and fluent professional English (B2 minimum; C1 preferred).

NICE TO HAVE (Preferred)

• Experience with Model Context Protocol (MCP), autonomous agents or multi-agent workflows.
• Scala, Kotlin or functional Java libraries such as Vavr.
• Elasticsearch, vector search/embeddings, Redis and performance optimisation.
• Docker, Kubernetes, AWS, Terraform and CI/CD.
• Experience integrating LLM-powered features into existing backend services.

Work model: Full remote across Europe, subject to contractual and country eligibility.

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