Germany
I help grid operators and large energy users, from data centers to battery developers, address the power-access crisis: grid capacity is maxed out, connection timelines stretch years, and traditional procurement can't keep pace with exponential compute growth. My focus: helping you connect, generate, and purchase power smarter and faster. As a Lead AI Engineer at E.ON, I design AI systems that help energy teams plan grid connections, optimize onsite generation, and make data-driven power procurement decisions - aspects that can make or break profitability of energy projects. My work bridges distribution and transmission operators with the fast-growing ecosystem of data centers, flexible loads, and renewables that are transforming the grid and creating mismatches between supply and demand. My background in computational science and high-performance computing gives me a unique lens: I understand the compute infrastructure now straining the grid from the inside. That foundation helps me see the scaling and energy challenges from both sides, where compute demands meet grid constraints. Through Powering Compute, I track the latest developments in datacenter connections and energy supply in Germany, helping grid operators and data center developers stay ahead of market shifts and infrastructure changes. 👉 Subscribe to Powering Compute for insights on datacenter power access in Germany, or connect directly to explore how AI can help with your grid planning, on-site generation and procurement challenges. Opinions are my own.
Serving Europe's citizens, democracies and environment by enabling compute growth that balances global competitiveness with citizen and environmental well-being at local and regional levels.
Coordinating and implementing GenAI initiatives within the Energy Intelligence team (Energy markets, assets, eMobility). Some of my responsibilities include: - Discovering use cases collaboratively with clients, and scoping effective implementations - Prototyping GenAI applications, including RAG, Agents, image generation and beyond - GenAI talent & upskilling strategy, and hiring - Aligning with top management to shape our GenAI strategy - Upskilling our engineers and data scientists in using state-of-the-art code generation techniques
At E.ON, my main responsibilities include: - Designing, implementing (Front-end, Back-end, ML), and striving for downtime-zero for our predictive maintenance product - GenAI Community @ data_on: Scouting company-wide for LLM use cases, organizing knowledge sharing sessions, and teaching internal trainings on "AI for software engineering" - LLMs @ Energy Intelligence: Collect, prioritize and validate LLM energy economics use cases in the areas of energy trading, flexibility trading, demand-side management, and smart grid security
At RBG, I leverage over a year of specialized experience with LLMs and RAG systems to bring AI-powered features to production. With a background in quantum machine learning and recent projects in AI auditing, I’m here to help you achieve sophisticated, metrics-driven solutions tailored to complex use cases. My approach is both lean and results-oriented, focusing on high-impact core competencies: Advanced RAG techniques, vector databases, long-term memory management, self-improving systems, and fine-tuning. Ideal for teams aiming to enhance AI capabilities quickly and efficiently, without drawing resources from essential projects. Past Happy Clients: AI Auditing (Stealth), Langfuse, Teleclinic
At NUA labs, we built AI replicas of busy experts to scale their one-to-one coaching. I was the only engineer, and held most product delivery and design responsibilities. My tasks included implementing state-of-the art RAG techniques (>90% answer relevancy), LLM production monitoring and tracing, product analytics, and vendor and model procurement and evaluation. Keywords: Langchain, Python, Llama-3, Cohere, Mistral, Ragas, Groq, Prompt engineering, Next.js, Docker, Software architecture, Microservices, Product management, User research
- Conducted 15+ user research sessions and designed a startup job marketplace - Functional leader for product and engineering, owning architecture and stack decisions - Implemented backend and frontend on Next.js, including monitoring, CI/CD, and product tracking - Grew the app to 350+ users, with an average of 9 daily active users