We are hiring a deeply technical AI Engineer to build production-grade ML systems that power real insurance claims decisions.We are supporting a Seed-stage company from the latest cohort of Y Combinator (S24), backed by leading global investors and scaling rapidly across London.They are not building AI demos. They are embedding AI into insurer operations at scale.What You’ll Work OnDesigning and deploying AI systems that directly impact claims accuracy and speed.Building production LLM-powered workflows (LangChain, orchestration frameworks, evaluation layers).Implementing classic ML/statistical models where appropriate. This is not prompt engineering-only.Building backend components required to productionise AI systems.Defining metrics, evaluation frameworks, and performance monitoring.We care deeply about applied ML rigour — not buzzwords.The Technical BarThere are many people who call themselves “AI Engineers.”We’re looking for those with:2+ years delivering ML systems from concept to production.Deep understanding of classical statistics and machine learning fundamentals.Clear thinking around evaluation metrics, bias, performance drift, and trade-offs.Comfort discussing model architecture, feature engineering, and system design.Ability to build backend systems supporting ML deployment.Culture & ExpectationsHigh-intensity, office-based.We hire slowly and expect alignment with startup realities.Strong ownership mindset required.You will work directly with founders who have already built and exited in the insurance space and have experience operating in regulated environments.Who Thrives HereEngineers who want to build AI-native systems from first principles.Former early employees or founding engineers.Builders who care more about impact and ownership than job titles.People aligned with the intensity of venture-backed startups.If you want ownership, velocity, and to help build the AI-native backbone of insurance, we want to speak with you.