About the role
About Motorway Motorway is the UK’s fastest-growing used car marketplace - our online-only platform connects private car sellers with thousands of verified dealers nationwide, ensuring everyone gets the best deal. Founded in 2017, our award-winning, technology-led approach has redefined the experience of selling a car. Motorway is backed by some of the world’s leading technology investors, having raised £143 million in Series C funding. This is a unique opportunity to join a fast-growing scale-up at a crucial phase of growth and help change an industry for the better.
About
the team GenAI Engineering sits within Motorway's Data and AI function, alongside Machine Learning and the Machine Learning Data Platform.
The team owns the GenAI features that shape how buyers and sellers experience the marketplace, spanning agentic workflows in the customer experience and LLM-powered tooling for our dealer network. Over the next two years the function scales from shipping AI features into running a serious GenAI platform. This hire is the technical authority who'll help shape that platform, working closely with engineering leadership across Data and AI and the wider Engineering org.
About
the role This is the most senior individual contributor role on Motorway's GenAI engineering ladder (IC5 / Principal). You'll report to the Director of Data and AI, advising the CPO and the wider exec on AI technical strategy. The remit is the trajectory of GenAI engineering at Motorway over a two-to-three-year horizon: the architecture, the standards and the strategic bets that no single team can absorb on its own. You'll set architectural direction across the GenAI surface area, hold sign-off on materially complex AI systems, and have the credibility to veto implementations that don't meet our agreed technical, safety or quality bar. You'll shape the high-stakes calls on vendor strategy, model selection, build-vs-buy on platform infrastructure, and our responsible-AI posture, providing the technical rationale that lets the Director of Data and AI and the wider exec land those calls with confidence. This is still a hands-on engineering role: you'll design and build the hardest single pieces of work directly, write production code on the systems that matter most, and pair with senior engineers on the architectural decisions that will outlast specific features. You won't own all AI usage at Motorway, you won't own overall AI strategy, and you won't hold budget for AI infrastructure, but you'll contribute meaningfully to all three, and you'll define how GenAI is built and evaluated here. This is a newly-created role and a greenfield opportunity. The technical bets you make will sit behind Motorway's most strategic AI initiatives, including ones not yet started. AI engineering choices at this level shape unit economics for years. In this role, you will: Set the overarching architecture for GenAI at Motorway, including reusable patterns for prompt design, RAG (hybrid retrieval, chunking, semantic caching), agent orchestration, evaluation frameworks (LLM-as-judge, golden datasets, adversarial prompts), guardrails and observability that other teams build on Design and build the hardest single pieces of work directly, taking on the problems nobody else is well-placed to solve and leading our highest-risk, highest-reward technical bets across the GenAI surface area Hold sign-off on architectural decisions for materially complex GenAI systems, with the credibility to veto implementations that don't meet our agreed technical, safety or quality bar Advise the Director of Data and AI on build-vs-buy calls for AI infrastructure (vector stores, eval platforms, AI gateways, model routers, agent frameworks), and own the technical rationale behind them Drive cost, latency and throughput optimisation across our production GenAI systems, with the trade-offs documented and explicit Define our principles for emerging paradigms, including multi-agent protocols, multimodal systems and agent-to-agent communication Define our responsible AI principles and keep us aligned with the EU AI Act, NIST AI RMF and ICO guidance ahead of regulatory deadlines Own opinionated relationships with our model and infrastructure providers, with the credibility to influence vendor roadmaps where it matters to us Coach engineers across the function, shape how we hire and review, and set the cultural bar for safety, evaluation and production quality Identify what Motorway should stop pursuing with the same clarity as what we should start, and represent Motorway externally through publications, conference talks and meaningful open-source contributions, used as a multiplier for hiring and partnerships About you Typically 8+ years building production AI/ML systems, with at least 2 years at the cutting edge of GenAI, and a track record of company-scale technical bets that have materially shifted a business's trajectory Strong engineering fundamentals and comfort working directly in code: Python and modern API-driven architectures on cloud infrastructure (AWS or equivalent), with the production engineering instincts (CI/CD, observability, SLOs, cost attribution) to take prototypes through to hardened production Current, hands-on expertise across the GenAI stack: LLM APIs, prompt engineering, RAG (hybrid retrieval, chunking strategy, semantic caching, re-ranking), agentic architectures (multi-step, multi-agent, tool use, memory), evaluation frameworks, LLMOps and fine-tuning Deep understanding of LLM capabilities and limitations, including how models fail in your domain, what hallucination and prompt injection look like in practice, and how to design evals that catch them Experience setting architectural standards adopted across multiple engineering teams over multiple years High-stakes build-vs-buy judgment, with a clear story of where you've been right and where you've been wrong Strategic grasp of responsible AI and AI governance, with practical experience aligning engineering decisions to NIST AI RMF, the EU AI Act or comparable frameworks Calm, direct communication with executive and board-level audiences, with the ability to compress technical complexity into the decisions leadership needs to make Coaching credibility with senior engineers, who have grown materially under your influence Self-awareness as a leadership trait; you know the limits of your knowledge and pull in outside expertise before that becomes a problem You could be a great fit if You have an external technical presence (publications, well-known open-source contributions or conference talks) and use it as a multiplier for hiring and partnerships You've led an organisation through a major AI paradigm shift in a previous role You have working knowledge of the ML Engineering and platform layer (serving infrastructure, AI gateways, cost attribution, multi-model routing) that GenAI features run on top of You've advised commercial leadership on vendor and partnership strategy, including contract and data-rights negotiation You've worked in a regulated, safety-critical or trust-heavy domain where AI behaviour has material business or legal consequence We offer a fantastic range of