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Senior Software Engineer / AI Enabler (m/f/d)
Senior Software Engineer / AI Enabler (m/f/d)
AutoScout24 is looking for a Senior Software Engineer / AI Enabler to join their Search & Performance group. This role involves optimizing the technology stack, supporting agile product development, and working on high-traffic systems that power the search experience and ad products. The ideal candidate will have deep expertise in Java and Spring Boot, experience with GenAI coding tools and LLM APIs, and a pragmatic view of AI's application.
About the role
About the Role
We’re hiring a Software Engineer to join Search & Performance group at AutoScout24 – the group behind the Algorithms and Data Quality that powers the AutoScout24 Search Experience and Ad Products. This role is about real ownership: you’ll work on high-traffic systems, shape key parts of our user experience, and contribute to critical business outcomes.
What you’ll do:
- Work on product and tech initiatives finding the right mix between effort, quality and user value
- Optimize and improve the AS24 technology stack by targeting individual and team efficiency, applying future proven concepts, architectural principles, and frameworks
- Support our agile product development approach
What you need to succeed:
- Deep expertise in Java and Spring Boot, with a breadth of knowledge across a range of languages and technologies in both Object-Oriented and Functional paradigms; able to quickly grasp new concepts and tools Experience with Scala is a plus
- 5+ years of Software Engineering experience, hands-on experience with PostgreSQL, DynamoDB, Kafka, and AWS is a strong plus
- Team player but also decisive mentality
- Demonstrated personal excellence in using GenAI coding tools (for example GitHub Copilot, ChatGPT, Cursor, OpenAI Codex) to significantly improve your own development speed and quality: code generation, refactoring, debugging, tests and documentation.
- Experience integrating LLM APIs (such as OpenAI, Anthropic, Azure OpenAI, Vertex AI or similar) into applications or internal tools.
- A pragmatic view of GenAI: you understand its limitations and risks and know how to put guardrails in place (reviews, tests, policies) to keep usage safe, compliant and sustainable at scale.