Lead Generative AI Engineer

Lead GenAI Engineer at Motorway shapes the architecture of the GenAI platform, setting the technical standard and solving the hardest AI problems. You will own production-grade systems that impact buyers and dealers, and mentor senior engineers to uplift the team. This role scales AI capabilities across squads, focusing on reliable retrieval, data quality, and cost-effective deployments. You’ll work in a fast-growing, data-driven environment with a strong feedback loop to continuously improve features.

• Competitive salary
• Equity scheme - shared success
• 25 days holiday
• Flexible working (London office 2 days/week)
• Private medical insurance via BUPA
• Life assurance`,`Pension scheme (contributes 5%)`,

• Set architecture standards for complex GenAI work across the function
• Sign-off on materially complex AI systems addressing safety, reliability, and production risks
• Own shared foundations: retrieval patterns, evaluation infrastructure, data pipelines, tooling
• Build the hardest components directly and act as technical escalation for tough problems
• Design for production-grade systems with graceful degradation, fallback behavior, and cost/latency considerations
• Develop senior engineers by giving challenging problems and constructive feedback
• Shape hiring and review practices with clear quality criteria
• Provide actionable industry insight on architectural planning and evolution of the GenAI stack

• Strong Python and SQL experience
• Deep GenAI expertise across retrieval at scale, vector stores, agentic orchestration, multimodal work, evaluation infrastructure, and fine-tuning
• Fluent in MLOps tooling, deployment, and cloud infrastructure (AWS and GCP)
• Track record of engineering production systems that withstood real-world production pressure
• Ability to explain hard technical trade-offs to non-technical stakeholders
• Self-awareness about knowledge limits and willingness to bring in experts early
• Ability to mentor and uplift other engineers and build a culture of high-quality work

• Clear communication with non-technical stakeholders
• Mentorship and leadership in multidisciplinary teams
• Hands-on, pragmatic problem-solving
• GenAI stack expertise
• Retrieval at scale
• Vector stores