Job Description

Our LINQ platform is the software that plans, schedules, and drives life-science labs. Our clients run labs for cancer diagnostics, drug discovery, cell manufacturing, and synthetic biology.

The stakes are physical: a bug in our code means a robot arm puts a plate of samples in the wrong place and a week of science is lost.

The prize is big: labs that run overnight and unattended, and scientists who get answers in days instead of months.

We're building the next generation of our core execution engine — one that recovers from anything a lab throws at it, with AI in and out of the loop, always opt-in: the deterministic core runs the lab on its own; models make it smarter. And that's just the start — vision that verifies the physical world, scientific models that design the next experiment.

The problems you'd be working on:

Scheduling that never stops. A scientist designing an experiment should never have to think about robots deadlocking — that's our problem, and it's a hard one. The science sets hard deadlines (cells must be fed, passaged, and imaged on time or they die), instruments overrun, and one cell-line maintenance process runs for months with hundreds of plates in flight. New work has to join a live schedule without stopping it — but whether a lab can deadlock depends on everything in it at once, so admitting a single plate means proving the whole world still holds. Get it subtly wrong and nothing crashes: two robot arms just wait on each other forever.

Throughput is the point. A safe schedule that leaves instruments idle wastes the lab. The engine has to execute as tightly as the constraints allow — overlapping steps, batching plates, keeping every instrument busy — because an idle instrument is science not happening. Safe-but-slow is easy; safe at maximum speed is the problem.

Recovery is the product. Anyone can execute the happy path. Labs pay us for what happens when a plate goes missing, an instrument fails mid-run, or a process has to resume after a restart. That means durable, replayable execution state, and recovery that reads the actual state of the physical world and replans dynamically — never follows a stale plan.

AI that's allowed to touch robots. Agents in the loop for error recovery, analysis, and designing the next experiment — exposed over MCP, grounded on the world model, gated by simulation. Our rule: AI proposes, the deterministic core disposes. An unverified model output never commands an instrument. Building the harness that makes that guarantee real is the interesting part.

The direction of travel: The Loop — hypothesis, execute, capture, analyse, decide, next experiment — closes with less and less manual glue, with human judgment applied where it matters most. Scientists focus on the science; LINQ runs the Lab.

The role:

Own end-to-end squad delivery within Product Engineering (Software), in a department with Product, Engineering, Design, Data & AI (PEDDA)—turning challenges into predictable, high-quality product delivery

• Hands-on squad leader–set the bar of what high-quality looks like at pace
• Own part of the technical architecture–set the direction of our product
• Partner with PEDDA, Customer Success, and Sales leadership to align on challenges, initiatives, and roadmap
• Lead, and level-up high-performing Product Engineers that report to you—hiring, mentoring, and setting an uncompromising bar for execution
• Architect, and continuously evolve operating systems that scale—eliminating bottlenecks, increasing velocity, and enabling the squad to move autonomously
• Embed AI-native and automation-first ways of working—unlocking step-change improvements in productivity and throughput
• Bridge strategy and execution—ensuring we build what we defined; that what we build, ships fast; and what we ship, delivers results with high quality

The stack:

We use the right tool for the job.

Our stack runs on Kubernetes edge clusters deployed in customer labs

• Go and Python services
• NATS JetStream is our event bus
• OR-Tools CP-SAT for constraint solving
• OpenTelemetry tracing end to end
• MCP for the agent surface, gRPC for driver surface, gRPC APIs, SDKs, CLIS
• Large fleet of robots and hundreds of lab instruments at the end of every code path.

You:

• You've architected and shipped a genuinely complex realtime or streaming system — and can talk about its failure modes for an hour.
• You want the whole stack, not a layer: the UI a scientist touches, the backend behind it, the engine, down to the drivers that move the machines — and you judge every layer by what it does for the user.
• You've taken complex features from idea to shipped, end to end — not incremental improvements to someone else's design — and you can point at the product impact.
• You don't wait for a PM to hand you a spec: you help shape the problem, push back when something doesn't feel right, and care about the speed and polish of what ships.
• Strong Go; Rust a bonus. You've integrated AI into products
• You've led senior engineers before and know the difference between leading and managing — you do the former from inside the code.
• You default to ownership: ambiguity is something you resolve, not escalate.
• 12+ years engineering, 7+ building products, in environments where both speed and quality were non-negotiable.

Logistics:

London, 3 days a week in office (near Angel).

Why this, why now:

• The problems are hard in the way that made you become an engineer: constraint solving, distributed state, realtime execution, physical consequences.
• The outcomes are real: our platform runs in labs working on cancer diagnostics, drug discovery, and synthetic biology. Faster labs mean faster science.

The team is small and senior, ownership is high, and the next-generation engine is being designed now — you'd shape it, not inherit it.

UK Team Benefits:

🍎 Vitality Health Insurance

👀 Eye Care

🚗 Salary Sacrifice - EV

🚲 Salary Sacrifice - Bike & Tech

🧘🏼‍♀️ Wellbeing & Support

☀️ Wellbeing & Development Allowance

💙 Spill & Employee Assistance Programme

😊 Additional Leave

👵🏼 Pension Scheme

🫂 Group Life & Critical Illness cover

We are an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Discrimination of any kind based on race, colour, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status is strictly prohibited.