Head of Engineering at VC-backed motorsport startup
About this role
who we are
Track Titan is building the operating system for motorsport – every racer's "personal career mode", from their first casual lap to the pro ranks. Over 300,000 sim racers use our AI coaching to get measurably faster – recording more than 1M km of racing telemetry daily while doing so, one of the most unique datasets in sports tech – and our ambitions stretch far beyond sim racing. We’re a team of pro-level racers who have also been senior employees in startups of all scales that have raised hundreds of millions of dollars. Together as Track Titan, we raised a $5M seed in late 2025, co-led by Partech and Game Changers Ventures, and we're the only company backed by tier-one VCs going deep on racing – which lets us make the big bets that nobody else in this space can. Now we're building the team to execute on those bets.
your mission
To build and lead the engineering org creating the best product in motorsport – one that ships quickly, predictably, and at a quality the whole team is proud of.
As our Head of Engineering, you'll own the people, delivery, and process side of engineering, across product engineering and ML. We're at the point where engineering leadership becomes a craft in its own right, and we're investing in it accordingly. You'll partner closely with the CTPO, who owns product and AI direction, to build the engineering org itself: the standards, the systems, and the culture.
This is a role for someone who is as passionate about speed, quality, team culture and operational excellence as most engineers are about the tech itself. The best teams are demanding and happy: people do their best work when expectations are high, ownership is real, and momentum is visible. We're not looking for someone to keep a machine running. We're looking for someone who is excited to build and fine-tune the machine in the first place.
Why this role, why now
We ship across web, desktop, and mobile, our ML work is moving from research into the product, and our ambitions are growing faster than the team. Our ways of working need to match: delivery that is predictable and visible, process that creates speed, and big ML bets that reach users in iterative steps along the way. We believe the fastest teams do fewer things, better – with high talent density and real ownership.
Up to now, engineering leadership has been shared between our CTPO and technical team leads, on top of everyone’s other responsibilities. This is the first time it becomes someone's full-time job – with real momentum and full backing from leadership.
What you will do
- Own and grow the team. Run 1:1s that go beyond status updates, give candid feedback early rather than at review time, and build growth plans people actually follow. Recognise excellence loudly and address underperformance directly and early – and make both feel like the same thing: taking someone's growth seriously.
- Own delivery. Own engineering's delivery cadence and commitments, across product engineering and ML. Make commitments clear, output predictable, and progress visible – momentum people can see is momentum they can feel. That includes research-heavy work: big bets broken into staged steps with honest uncertainty, so that user value ships along the way and decisions to double down, pivot or stop come early. When something slips, find the systemic cause and fix it rather than managing around it.
- Build the operating system. Own the culture, rituals and processes that make the team fast – planning, retros, definition of done – improving them by shipping changes, not just writing proposals. You know the difference between process that creates speed and process that creates paperwork, and you treat process debt with the same seriousness as tech debt. This should be the part of the job that excites you most – especially at a time when AI is reshaping how engineering orgs are built and operate.
- Lead how we build. Own org-wide standards and practices – quality, reliability, infrastructure and cost – and lead how we build as an AI-native engineering org. This is a hands-on management role, especially early on: you'll spend real time in the codebase and work closely with our senior engineers on the technical decisions that matter most.
- Raise the bar with every hire. Own engineering's hiring and onboarding. Every person you add should lift the average, not just fill a seat, prioritising talent density over headcount. We expect engineering to grow significantly over the next 12–18 months, organically and potentially through acquisitions, and you'll shape who joins and how quickly they're shipping and feeling at home.
- Put the team on the map. How we show up externally – through an engineering blog, conference talks, open source, or something we haven't thought of – is a fairly blank canvas and yours to shape together with the team. A team proud enough to show its work attracts people who raise the bar further.
What success looks like in your first six months
- Delivery is predictable, visible, and measurably faster: commitments are clear and met, and we ship user value in regular increments while also working towards bigger bets with more uncertainty.
- Our levelling and performance systems are built for a growing org, and the team trusts them.
- You've made your first hires, and each one lifted the average and delivered user impact.
- We can absorb new people, teams and codebases – organically or through acquisition – without losing speed.
- How we build and run things with AI is something the team is proud of, and that others ask us about.
your profile
What you bring:
- Strong track record of managing software engineers, including leading multiple teams or managing managers – and management is the job you are passionate about, not the one you drifted into. The engineers you've managed would sign up to work for you again.
- You've both taken over an existing team and built one through hiring, and you know the difference. You can talk concretely about how you earned trust in a team you didn't hire, and how you raised the bar through the people you brought in.
- You've made a team measurably faster. You can point to delivery you improved – predictability, scoping, cycle time, the quality of commitments – and explain what you changed and why it worked.
- You hold a high, explicit bar – and people rise to it rather than resent it. You'd rather have a hard conversation this week than a harder one next quarter, and you make performance – strong and weak – visible rather than letting it blur. Your former teams would call the experience demanding, and mean it as a compliment.
- You've built people-systems, not just used them – engineering ladders, how feedback flows, how work gets planned and reviewed – ideally somewhere they didn't exist yet.
- You're technically strong and hands-on. Ideally you've been a strong senior or staff engineer yourself: you can go deep in the stack, pressure-test architecture and delivery risk with senior engineers, and be taken seriously. You don't need to out-code the team, but you can't be a pure process manager.
- Startup-scale pragmatism. You're comfortable in a small, early-stage engineering org while designing for one many times its size. No playbook cargo-culting: you understand the principles behind the processes and adapt them to the stage we're at.
- Excellent written communicator. As a partially distributed, async-first team, writing is how we work: documentation, expectations, decisions, and feedback all live in writing.
- Fluency with AI, both in your own work and in how it reshapes engineering orgs. You have a strong point of view on how AI changes how engineering teams should be structured and operate, ideally with concrete examples from previous teams. We're an AI company and we expect everyone to work like one.
- You're obsessed with the product and its users. You use what you build – regularly and critically. For us that means driving: everyone on our team gets in the sim and uses Track Titan the way our racers do. Dogfooding is part of our culture.
- You've delivered predictably where outcomes are uncertain. You've led ML, data science or research-heavy work into production alongside product engineering. You don't need to be an ML expert, but you know how to run this kind of work.
- You've operated at the leadership level. You've owned an engineering budget, reported delivery and risk to execs or a board, and been through technical due diligence or integrated an acquired team.
- Motorsport passion. Ideally you're already a sim racer or motorsport fan. If that’s not the case yet, what matters is genuine curiosity and that you go deep fast. If you don’t think you will find this interesting, then this is likely not the role for you.
- Based in London. We're fully remote flexible (including some global members), but regular presence at our London HQ is a strong plus for this role.
why us?
- Build the engineering org at a defining moment. You won't inherit a heavy legacy structure – you'll create the systems the org runs on for years, with org-level ownership from day one.
- Leadership that wants you to win. You'll partner directly with a technically deep CTPO whose focus is product and AI direction – meaning engineering execution is truly yours to own – and you will also be close with the CEO and the commercial team who count on you for honest views on what engineering can deliver and when.
- Work worth showing. Exciting technical challenges, one of the most unique datasets in sports tech, and a product that reaches hundreds of thousands of racers across the globe 24/7.
- Join a team of fellow motorsport fans and sim racers who have backgrounds in top startups, sports data science, tier-one consulting, and professional motorsport, at the only motorsport startup in the world backed by tier-one VCs
- Quarterly learning day and budget
- Remote/office flexibility according to what works for you, with a great London HQ
- Generous options package as a key early employee
- Private pension (for UK employees)
- Private health insurance (for UK employees)
Originally posted on Himalayas
