AI Engineer
EQT Ventures is the early-stage venture capital strategy of EQT Group, partnering with founders building 'Generation-Defining Companies.' With 1.1 billion euro invested behind the strategy, EQT Ventures acts as an early-stage lead investor, operational advisor, and high-conviction capital provider for ambitious European founders, typically investing between 2-50M EUR.
About EQT Ventures
EQT Ventures partners with founders building Generation-Defining Companies, aiming to back ambitious visions that can become game-changing, resilient businesses. As early-stage lead investors, operational advisors, and high-conviction capital providers, the team—made up of ex-founders and operators—provides hands-on support to help portfolio companies scale fast, break through barriers with access to the global EQT platform, and build long-term resilience. EQT Ventures is domiciled in Luxembourg, with investment advisors located in Stockholm, Paris, London, New York, Berlin and Amsterdam, and is focused on European companies, having backed over 140 founding teams to date across sectors such as AI, fintech, edtech, robotics, and aerospace. The firm operates through multiple funds, including EQT Ventures I, II, and III, with clients/portfolio companies ranging from early-stage startups like Sana Labs, 1X, Payrails, Parloa, and The Exploration Company.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build AI products and platform capabilities from idea through production. You will work directly with users to identify opportunities, prototype useful solutions, and turn successful experiments into reliable, reusable, and scalable capabilities. You will connect models, internal systems, APIs, data sources, and tools to support real business workflows. You will independently own projects while collaborating on the underlying platform and technical foundations.
Requirements
- Strong software engineering skills with practical Python and modern application development experience
- Hands-on experience with language or multimodal models, model APIs, retrieval systems, agents, or related AI tooling
- Experience with APIs, databases, backend services, data pipelines, or cloud infrastructure
- Sound engineering judgment for reliable, observable, and maintainable systems
- Clear written and verbal communication skills for working with non-technical colleagues
- Ability to own loosely defined problems and rapidly build useful working products
Responsibilities
- Build AI tools alongside users and learn from real-world use
- Prototype and ship agentic systems using the in-house AI harness
- Turn unstructured business material into agent-ready information
- Connect internal systems, vendor products, APIs, and data sources for AI systems
- Turn successful experiments into scalable shared platform capabilities
- Own projects independently and collaborate on platform foundations