AI Build Lead

The Role

The gap between the engineering manager, the product owner, and the hands-on builder is closing fast, and this role is for the person already operating in that mode. You lead the team, own delivery, and write the production code that puts the product in front of real customers. This is not three jobs crammed into one. Multiverse has built an environment where AI-native ways of working collapse the old boundaries, so one person can own the whole arc from idea to live product. The Scotland hub exists to build AI-native products like this one and set the practices that make the company AI-first.

You partner with the leadership to shape the vision and own how it comes to life. The north star is still taking shape, so there is real room to influence what the product becomes while you build it, with a tight loop between customer feedback and what you build next.

As a player-coach, you line-manage and grow a small core team while staying in the code, pulling in other engineers and specialists as the work needs them. The team is assembled around this problem and runs a compressed, AI-native delivery loop: ideation to production in days not quarters, experimentation over debate, and an obsession with the right outcome rather than the perfect solution.

We embrace a “re-teaming” culture, giving you the high-agency opportunity to dynamically form teams around business priorities, tackle new disciplines, and drastically accelerate your career trajectory.

What You Will Do

Own delivery of the product.

You bring the product vision to life for real apprentices, customers and coaches. You own discovery, build, launch, and the calls on what to build next. You are accountable for impact and not just for shipping on time.

Lead the team as a player-coach.

You line-manage and grow a small core team while staying in the code, and pull in other engineers and specialists as the work needs them. You set the standard in the work itself, and create the psychological safety and guided autonomy that let people own their decisions.

Ship production code yourself.

Prototypes, proofs of concept, and production agents in the same repos and behind the same gates as everyone else’s. When building the thing is the fastest way to learn or unblock the team, you build it.

Read the customer and run a fast build loop.

You stay close to how customers, learners and coaches use the product and let that drive what comes next, using AI-native discovery: deep research agents, conversational research at scale, and analytics that go past the dashboard. The loop runs from idea to production in weeks, scored against real usage rather than argued in a meeting.

Help shape how Multiverse works AI-native.

The ways of working that make this role possible are constantly being refined. You contribute the patterns, tooling, and operating model, prove them in how your own team runs, and share what works with the wider org.

What We Are Looking For

Product Ownership

You have delivered a customer-facing product end to end, and you are at your best taking an early vision and making it real. You decide what to build next from what customers actually do rather than from a roadmap fixed in advance, comfortable moving between the north star and the build. No product management title required. What matters is a product with your fingerprints on the outcome.

Production AI Engineering

You ship production code and understand what makes AI product engineering its own discipline: context management, model selection, tool design, evaluation of agent output, and the token economics that separate a prototype from an affordable production system. You do not need to architect a multi-agent platform from scratch — that depth sits with the Principal and Staff engineers — but you build what you want to test and get it live without an engineer rebuilding it first.

Player-Coach Leadership

You have led and grown engineers while staying hands-on, setting direction and coaching without disappearing into management. You create psychological safety and guided autonomy by default, give direct feedback well, and grow people because you are close enough to the work to do it credibly.

AI-Native Delivery

You build with Claude Code, or the equivalent of the week, daily and well: worktrees, context steering, critical review, evals kept running. You have run delivery in tight loops where bets are cheap to test, failure is recovered from quickly, and progress is measured by outcomes rather than output. The bar is the one the AI engineering team holds itself to, and the product and leadership weight of the role buys no exemption from it.

Communication

You explain product and technical calls clearly to engineers and the senior leaders you work with, write briefs that move decisions forward, and hold your ground with a Principal engineer without needing to be the most technical person in the room.

What Would Set You Apart

• Founding engineer or founding product hire at a startup that shipped real product, or the engineer-PM-lead hybrid on a small team
• A track record of coaching other managers or engineers through the shift to AI-native ways of working
• Public thinking on how the manager, product, and builder roles converge in an AI-native org
• Experience in EdTech, regulated content, or domains where AI output quality has compliance or accreditation implications
• Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards

What We Are Not Looking For

• Traditional engineering managers who run delivery and ceremonies but do not own a product or write code
• Pure product specialists who will not lead a team or build, or Principal and Staff engineers who want to anchor architecture rather than lead a product; both have a better home in other roles
• People who treat AI tooling as a productivity tweak rather than a step change in how a team works
• People who need a detailed spec and a sprint plan before starting; this role writes the brief