Co-Founder & CTO @ AI Model Efficiency Engine 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, even before the next generation arrives. That is the opportunity we are building around. We bring closed providers and open-weight models together behind a single API. With no proprietary model to promote, we can choose the right combination for the task. 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 result against agreed quality standards. Think ten specialists working on ten pieces, rather than one generalist carrying the whole 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, and brings considerable drive, a hands-on approach and a strong sense of urgency to building the company. We closed our pre-seed round in two weeks. With people already waiting to use the product, we are looking for a technical co-founder to help shape what comes next and bring it into production. About the Role As co-founder and CTO, you will help shape the company as well as its technology. Working alongside the founder as an eye-level partner, you will turn the ambition into an architecture, a product and an engineering team capable of delivering it.a Your remit spans the efficiency engine, the platform beneath it and the people building both. You will lead our founding AI engineer and backend platform engineer, grow the team and establish the standards that guide its work. You have led engineering before, but stayed close to the code, and want to keep building as your responsibilities grow. Two things define the technical challenge here. Efficiency is the product itself, so routing, fine-tuning, caching, quantization and open-weight serving sit at the heart of the roadmap. Agentic engineering is also central to how we work. You will set the standard for using individual agents and entire agent fleets effectively, building the harnesses and workflows that allow a small team to move quickly while retaining sound engineering judgement. There is a lot to build and an ambitious timeline ahead. We work with relentless intensity, move quickly from decisions to execution and look for people who take initiative and see things through. You will have the scope to make consequential decisions early, and the responsibility to turn them into something that works. What you’ll do You will move between architecture, code and company building, setting the technical direction while building the team that delivers it. Lead the engineering team: guide our founding AI engineer and backend platform engineer, review their work and establish the engineering and operational standards, including on-call and incident response. Build the team: lead technical hiring and decide how engineering grows as the company develops. Set the technical direction: make the architectural calls, shape the roadmap and decide what we build ourselves and where we use existing tools and services. Develop the efficiency engine: bring together routing, semantic and prefix caching, parameter-efficient fine-tuning, distillation, quantization and batching, with inference economics informing each decision. Own open-weight serving: choose and operate vLLM, SGLang or equivalent, including GPU capacity and European hosting, alongside closed providers through a single interface. Make quality measurabl