Senior AI Engineer, London

About hyperexponential (hx) At hyperexponential, we’re building the AI-powered platform that enables the world’s most critical decisions in a $7 trillion industry, which risks to take, and how to price them. These are the decisions that shape real-world outcomes: whether rockets successfully launch into space, autonomous vehicles make it to market, or communities recover after major storms. Until now, insurance has been making billion-dollar decisions using outdated tools. We’re changing that. Our platform brings together data, AI, and human expertise to give insurers the fastest path from submission to decision - helping them move faster, act smarter, and take on more risk with confidence. Backed by a16z, Highland Europe, and Battery Ventures, we’re scaling globally - already trusted by nearly 50 of the world’s largest insurers, with zero churn and billions in premiums flowing through hx. What began as a single product in one market has rapidly evolved into a multi-product, multi-territory platform powering every stage of pricing and underwriting. AI is at the core of what we do - from building the world’s first domain-specific AI peer programmer for insurance (think GitHub Copilot with a PhD in actuarial science) to shaping agentic workflows that reinvent how this industry operates. What makes hx different is the people who build it. Here, impact isn’t tied to title or tenure; it’s defined by the challenges you take on and the discipline you bring. Surrounded by peers who stretch you, you’ll do the best, hardest work of your life in a company engineered to endure. If that sounds like you, join us in building what comes next. About the hxAI team At hx, AI is not an add-on, it is central to our mission. We are redefining how the insurance industry builds software and makes decisions, powered by generative AI. Our team combines state-of-the-art LLM technology with deep insurance domain expertise to solve problems no one else is tackling. We’re currently focused on two flagship products. The first is a powerful ingestion engine that transforms unstructured insurance documents into structured insights. The second is our crown jewel: a domain-specific AI peer-programmer embedded inside a custom IDE, designed to reshape how actuaries and underwriters code, model risk, and make billion-dollar decisions. This is applied AI with teeth. Our team moves fast, experiments often, and ships real value into the hands of customers. You’ll join a small, high-ownership group with the autonomy to drive innovation and directly influence how AI transforms an entire industry. What you’ll be doing Architect and scale advanced AI and ML systems that power hx’s next generation of products - solving problems where no off-the-shelf solution exists. Lead the design and deployment of cutting-edge model capabilities, from LLM-driven workflows to domain-specific ML pipelines optimised for messy, high-value real-world data. Drive foundational decisions across data, modelling, and production infrastructure to ensure performance, robustness, and long-term scalability of our AI platform. Rapidly prototype novel ideas, validate them in live environments, and evolve successful experiments into production-grade systems used by customers at scale. Advance hx’s broader AI strategy: shaping technical direction, embedding best practices, and raising the bar for how we build, test, and ship ML-powered features. Act as a technical multiplier: mentoring engineers, cultivating deep ML craftsmanship, and fostering a culture anchored in curiosity, speed, and scientific rigor. What you’ll need to have done Built and operated production-grade ML products in Python, with deep expertise across software development, model development, data processing, evaluation, and optimisation. Designed and scaled distributed, cloud-native pipelines - bringing clarity and structure to ambiguous real-world data challenges. Taken full ownership of impactful AI initiatives: from identifying the opportunity, to modelling, to deploying and measuring value in production. Communicated complex ML concepts clearly and persuasively across engineering, product, and business teams. Influenced technical direction and culture, translating local wins into durable engineering practices. Delivered AI/ML-powered products end-to-end, balancing rapid experimentation with the demands of high-reliability production systems. (Nice to have) Brought LLMs into production, especially for NLP-heavy or retrieval-augmented use cases. You’re unlikely to thrive here if You prefer predefined playbooks and predictable projects over ambiguous, exploratory work. You see your contribution as limited to code, rather than shaping products and systems end-to-end. You’re uncomfortable with rapid iteration and experimentation in live environments. If reading our Culture Document leaves you feeling neutral rather than energised, hx may not be the place where you’ll do your best work. We’re building something that a