Junior Applied AI Engineer (all genders)
HybridKronberg, Hesse, Germany
Job Summary
Use AI coding assistants daily as a standard part of delivery, actively integrating LLM APIs into production applications while managing token limits and latency. Apply AI across the full software delivery lifecycle, including AI-generated tests, debugging, code review, and prompt engineering, while owning the quality and reliability of AI outputs. Define and track KPIs to evaluate the effectiveness and ROI of AI-assisted workflows, presenting metrics to stakeholders. Own end-to-end delivery from design through production support in Agile sprint cycles alongside client teams. Build application layers and interfaces connecting full-stack systems to agentic backends, understanding data flows and integration points.
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field
- Exposure to commercial software engineering experience in production environments (or equivalent demonstrated through academic projects, internships, or shipped personal projects)
- Proficiency in at least one primary backend language: Python, Java, or TypeScript
- Demonstrated hands-on experience using AI tools actively in day-to-day engineering work — with practical examples of how AI was used to solve real problems, iterate on outputs, and improve delivery
- including direct experience calling LLM APIs in production code with an understanding of token management, latency, and cost tradeoffs
- Basic understanding of web technologies including JavaScript, HTML, and CSS
- Familiarity with cloud fundamentals (AWS, Azure, or GCP), containers (Docker), and CI/CD pipelines
- Understanding of Agile delivery fundamentals
- Experience with databases — SQL or NoSQL
- Ability to validate, evaluate, and improve AI-generated outputs
- understanding of AI limitations and responsible use
- Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture
- production experience preferred, conceptual understanding required
Desired Qualifications
- production experience preferred, conceptual understanding required
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