Lead Generative AI Engineer in London

Lead Generative AI Engineer in London

London Full-Time 81000 - 99000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the development of innovative GenAI features and set technical standards for the team.
  • Company: Join Motorway, the UK's largest online car-selling platform, transforming the industry since 2017.
  • Benefits: Enjoy competitive salary, equity scheme, flexible working, and generous holiday allowance.
  • Other info: Collaborative environment with opportunities for professional growth and a focus on team success.
  • Why this job: Make a real impact in a fast-growing scale-up and shape the future of AI in car sales.
  • Qualifications: Strong experience in Python, SQL, and GenAI technologies with a passion for mentoring others.

The predicted salary is between 81000 - 99000 £ per year.

About Motorway Motorway is the UK's largest online car-selling platform.

We connect private sellers directly with over 8,000 dealers nationwide.

Our online platform helps sellers achieve great prices for their cars while giving dealers fast, reliable access to the stock they want for their dealerships.

Founded in 2017, our award-winning, technology-led approach has redefined the experience of selling a car. the company 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 Gen AI Engineering sits within the company's Data and AI function, alongside Machine Learning and the Machine Learning Data Platform.

We own the AI features that shape how buyers and sellers experience the marketplace, from agentic workflows in the customer journey to LLM-powered tooling for our dealer network.

What we build goes into the hands of real sellers and thousands of verified dealers, usually within weeks.

When it works, someone sells their car more easily.

When it doesn't, we hear about it.

That feedback loop is short, and it shapes how we work.

We have a track record of successful deployments and a strong reputation as a result.

Over the next two years the function scales from shipping AI features to running a serious Gen AI platform.

About the role

We're looking for a Lead Gen AI Engineer to set the technical standard for AI work across the function, and to build the hardest parts of it themselves.

You’ll own the architecture and standards for complex, product-facing Gen AI work.

You’ll hold sign-off on the systems that carry real risk, and you’ll be the person a squad comes to when they’ve hit something genuinely hard.

This is a player-coach role: your own code sets the bar others refer back to, and you’ll spend as much energy making senior engineers better as you do building.

Most of what makes a Gen AI feature good sits around the model rather than in it.

The prompting is rarely the hard part.

Retrieval quality is, and so is the data feeding it, evaluation you can trust, sensible behaviour when things fail, and getting it live and keeping it there.

The standards that matter most here are the ones that make that work repeatable across teams.

We’re not precious about the route you took to this kind of engineering.

You’ll report to the Engineering Manager for Gen AI Engineering, partnering closely with the Principal Gen AI Engineer, the Director of Data and AI, and product leadership.

  • In this role, you will
  • Set the architecture standard for complex Gen AI work across the function, not by mandate but by building things others learn from and want to adopt.
  • Hold sign-off on materially complex AI systems, catching architectural, safety and reliability problems before they reach production.
  • Own the shared foundations that determine feature quality across teams: retrieval patterns, evaluation infrastructure, data pipelines, and the tooling that makes good practice the easy path.
  • Build the hardest pieces of work directly, acting as the technical escalation point for the function’s toughest problems.
  • Design for systems that stay up and stay affordable, covering graceful degradation, fallback behaviour, and cost and latency at production scale.
  • Develop the senior engineers around you by handing them harder problems, room to own decisions, and honest feedback.
  • Shape how we hire and review, bringing a clear and defensible view of what good looks like.
  • Bring specific, actionable industry insight into planning, explaining what a development means for our architecture rather than noting that the field moves fast.

About you

  • You've set technical direction that other engineering teams actually adopted, and you can talk about where that worked and where it didn’t.
  • Strong Python, and SQL you genuinely use. A lot of this work is data work: grounding data, golden datasets, and understanding why something failed.
  • Deep, current expertise across the Gen AI stack, including retrieval at scale, vector stores, agentic orchestration, multimodal work, evaluation infrastructure and fine-tuning where it earns its place.
  • You’re fluent in the layer underneath: MLOps tooling, deployment and cloud infrastructure (we run on AWS and GCP), and you can tell the difference between a choice that matters and one that doesn’t.
  • You design systems that survive contact with production, and you’ve been on the hook when they didn’t.
  • A strong point of view on evaluation, including the difference between evals that catch regressions and evals that provide comfort.
  • Your direct contributions set a quality bar for the people around you.
  • You explain hard technical trade-offs to non-technical stakeholders without either condescending or losing the substance.
  • Self-awareness about where your knowledge runs out, and the instinct to bring in expertise early.
  • You could be a great fit if
  • You build with taste, preferring simple systems that work over clever ones that nearly do.
  • You use authority sparingly. You’re not a blocker, but you’ll stop a bad decision from shipping.
  • You get satisfaction from the unglamorous work that makes AI features actually good, not just the part that demos well.
  • You enjoy making other engineers better as much as building things yourself.
  • You’ve levelled people up in a way they’d recognise, whether through a talk, a review, or how you work day to day.
  • You hold a two-to-three-year view without losing touch with what’s shipping this month.

BENEFITS

  • Competitive salary
  • Equity scheme - we all share in the company's success
  • 25 days holiday
  • Flexible working (2 days a week in our London office, with socials and snacks galore)
  • Private medical insurance via BUPA
  • Life assurance
  • Pension scheme (we contribute 5%)
  • Enhanced family leave (e. g. 26 weeks full pay for maternity or adoption)
  • 24/7 Employee Assistance Programme
  • EV leasing scheme
  • Cycle to work scheme
  • Nursery salary sacrifice scheme
  • 1 paid volunteering day a year
  • #J-18808-Ljbffr

Lead Generative AI Engineer in London employer: United States Digital Space LLC

At our company, we pride ourselves on being an exceptional employer, offering a vibrant work culture that champions diversity and inclusion. With a strong focus on employee growth, we provide clear career paths, personal learning budgets, and generous benefits such as private healthcare and a flexible work-from-abroad policy. Join us in London and be part of a team dedicated to making a positive impact through greener travel choices while enjoying the perks of a supportive and innovative environment.

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Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Generative AI Engineer in London

Join Local Tech Meetups

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Contribute to Open Source Projects

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Explore Job Boards Specifically for Tech Roles

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We think you need these skills to ace Lead Generative AI Engineer in London

Python
SQL
GenAI Stack Expertise
Retrieval at Scale
Vector Stores
Agentic Orchestration
Multimodal Work

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at United States Digital Space LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at United States Digital Space LLC

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If United States Digital Space LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.