Technical Co-Founder (AI Efficiency) @ AI Venture, Berlin

This is an Atlantic portfolio venture. About the Venture AI models have moved faster than most companies’ ability to put them to work. The capabilities are there; knowing how to combine them effectively is still catching up. Frontier labs naturally put their own models first. Companies often follow suit, asking one general-purpose model to handle ten very different jobs. We believe there is far more to unlock in the models that already exist. We bring closed providers and open-weight models together behind a single API. Our engine breaks requests into their component parts, routes each to the right model within a cost budget, fine-tunes on customer data and checks the results against agreed quality standards. With no proprietary model to promote, we can choose the best combination for each task. Lower costs matter because of what they make possible: giving a small team the freedom to build something that would previously have required a much larger one. Our founder was selected for Slush 20 Under 20, awarded by Anthropic, Slush, Index Ventures and Sifted. We closed our pre-seed round in two weeks and already have people waiting to use the product. We're now looking for a technical co-founder to help turn this opportunity into a company. About the Role As Technical Co-Founder, you will lead the development of our AI efficiency engine, working alongside the founder to turn a compelling technical opportunity into a product. At the heart of the role is a deceptively simple question: how can we make AI models deliver the same or better results at a fraction of the cost? You will explore approaches to model routing, fine-tuning, caching and inference optimisation, combining scientific curiosity with the ability to turn promising ideas into measurable improvements. This is a role for someone who enjoys difficult technical problems, rigorous experimentation and challenging existing approaches. You won't be expected to build every part of the platform yourself. Working alongside our founding AI engineer and backend platform engineer, you will set the technical direction and focus your expertise where it creates the greatest impact. Agentic engineering is central to how we work. We're looking for someone who already operates this way, using coding agents and developing the workflows and harnesses that allow a small team to move exceptionally quickly without compromising technical quality. Above all, this is a co-founder role. We're looking for someone who wants to take genuine ownership, work with relentless intensity and help build a company from its earliest stages. What You'll Work On Drive AI cost efficiency: develop approaches to reducing inference costs through model selection, routing, caching, fine-tuning, quantization and other optimisation techniques. Experiment and benchmark: design rigorous evaluations to understand the trade-offs between cost, quality and latency, turning technical insights into measurable improvements. Shape the efficiency engine: determine how closed and open-weight models can be combined and optimised to deliver the best outcomes for different tasks. Set technical direction: identify promising opportunities, make key architectural decisions and guide the founding engineers in bringing them to production. Push agentic engineering forward: use coding agents as a core part of your work and develop the harnesses and workflows that allow a small team to operate with exceptional leverage. Build the company: work closely with the founder on technical strategy, attract exceptional talent and help shape the product and business. About You You bring deep technical curiosity, scientific rigour and an entrepreneurial mindset. You enjoy getting into the details, testing hypotheses and finding approaches others might overlook. We're particularly interested in people who bring: Deep expertise in AI efficiency: meaningful experience optimising the cost or performance of LLMs