Platform Engineer

About Us

We believe that the way to win the AI revolution is to automate not others, but ourselves. Our arena is complex megaprojects. We automate what we can and do old-school what we must. We build AI tooling to take our own jobs — the tools and knowledge that teams of humans and AIs need to run megaprojects.

Our product consists of two halves:

• A customer-facing platform that runs both standard and bespoke project scheduling apps, supports large-scale datasets, complex integrations and large groups of users and runs an AI copilot.
• An internal AI operating system that automates and supports our own work. It dials into meetings, analyses customers' screen-shares and shared datasets, builds implementation plans, orchestrates coding agents and validation systems — and pushes PRs. This is the software that will take our own jobs.

We're a small team in London, growing fast, and looking for people who want to build things that make a difference on megaprojects. We're a team of people who see a problem and run at it — figuring things out, and not stopping at “that's not my job.” Our current team is small (4 people) — so any new joiners can make a big difference. Our Q1 revenue was 4x our Q4 revenue, and we just raised our Seed round at a ~$25m valuation. The next step is to aggressively scale the business.

Our customers are (mostly) large general contractors, infrastructure builders and asset owners. They build rail lines, airports, power plants, solar farms and more. We work with them to improve the construction schedules for these assets.

The Role

The Platform Engineer builds and improves our platform. The platform covers anything that makes customer delivery fast & high-quality. This includes our internal AI operating system (the software that is stealing our own jobs), our customer-facing AI agent (“cursor for project management”), shared component library (large-scale optimisers, rendering pipeline for large datasets, …), deployment & hosting system (single-tenant VPCs for complex customers, different infra requirements for data sovereignty, …) etc.

We need engineers who are high in conceptual understanding — and even higher in a willingness to work on very diverse engineering challenges.

Platform engineers work mostly heads-down on the platform, while supporting the customer-facing team when something requires deeper platform-level changes. As a small team, our platform engineers are expected to participate in supporting the customers when needed.

What We Offer

• Salary ranging £100k to £160k for promising profiles
• Share options ranging from 0.5% – 1.0% (4-year vest, 1-year cliff, fully diluted)
• Nice office in London (some flexibility on hybrid)
• Skilled worker visa sponsorship if needed — we have as many nationalities as people in our current team
• Highly entrepreneurial environment
• All the equipment, software and tokens you need to do the best job
• Unlimited headroom to grow

Problem Domains

• AI agents, algorithms, scheduling optimisers, and computational logic
• Infrastructure, deployment, scaling, and system architecture
• Product-facing shared components: minimising friction, designing reusable patterns
• Internal delivery operating system: the tooling PlanLab uses to run its own engineering and delivery
• All our code is strongly typed (TypeScript, some Rust), which we deploy on various infra providers

What We're Looking For

• Strong engineer with broad skills across the stack
• Product-minded: enjoys thinking about what to build, not just how
• Comfortable making irreversible decisions with incomplete info
• Can own features end-to-end, from design through deployment
• Can debug across layers (infra → product → model)
• Comfortable context-switching across different problem domains

Ideal Backgrounds

We like people who have built, shipped and maintained/operated systems that had to work in the real world — under time pressure, unclear requirements, and imperfect data. We care less about background and more about whether you've repeatedly turned messy problems into working solutions.

Your First 90 Days

In your first 3 months here you might:

• Improve our end-to-end service delivery automation AI (e.g. so it can ask customer design questions in live meetings, so it can record videos of new demos, so it can automatically generate project delivery plans)
• Support delivery leads on complex customer features (e.g. new visualisations needed, deliver an integration with another piece of software such as SharePoint)
• Improve our deployment & hosting setup (e.g. improving testing setup so AI agents can iterate faster, make it easier to deploy to a given market with specific feature requirements, improve our coding agent sandbox)