Senior AI/ML Engineer (m/f/d)

Job description

Your mission Most AI lives in a chat window. Ours will run physical infrastructure across a pan-European network. As a Senior AI/ML Engineer in our newly established AI UNIT within E.ON Drive Infrastructure (EDRI), a special unit built and run like a startup, you will be at the forefront of designing, building, and scaling AI systems that deliver real business impact. Working across the entire AI lifecycle, you will take solutions from experimentation to production and own them there, while helping define the technical foundation of our AI UNIT. You report to our Head of AI Strategy. Your Responsibilities Shape the AI/ML architecture, technology stack, and engineering standards of the unit Design, build, and operate production-grade AI and machine learning systems and own their reliability, quality, latency, and cost Develop classical ML and GenAI solutions, including RAG, agentic systems, and AI-powered services Productionize ML models developed by our Data Scientists and operate them at scale Define and enhance MLOps and LLMOps practices for deployment, versioning, monitoring, evaluation, and retraining Own our LLM gateway, including model routing, token limits, cost per use case, guardrails, and logging Build scalable AI services and APIs for our Full-Stack and AI Deployment Engineers Evaluate emerging AI models, AI tooling, and agentic systems and integrate impactful innovations into our stack Share knowledge and support the growth of junior colleagues – this is a senior individual contributor role Your profile You are an experienced AI engineer who combines strong software engineering fundamentals with hands-on expertise in modern machine learning and Generative AI. You enjoy solving complex problems, taking ownership, and turning ideas into production-ready solutions. Must have Proven experience owning AI/ML solutions in production end to end, with measurable impact Strong software engineering skills in Python, including testing, CI/CD, and clean architecture Solid understanding of machine learning concepts, model evaluation, and experimentation Production experience with Generative AI, including prompting, RAG, agents, and evaluation frameworks Experience with MLOps and model deployment workflows in Azure – AWS or GCP experience transfers Strong understanding of trade-offs between accuracy, latency, scalability, cost, and risk Ability to translate co…