Job description
The opportunity
We're a stealth startup in AI and bio, building infrastructure for data generation. The team is small and elite, the problems are hard, and the foundations are being laid right now. You'd help write them from the first line, with real ownership and a direct line to the founders.
About us
AI for biology has a data problem. The data that matters most doesn't exist yet, so we're building the infrastructure to produce it, with quality and traceability built in from day one.
We're in stealth and heads-down on execution. We'll share more about what we're building once you've spoken with the team.
What you'll do
You will build the core software behind our lab, working across the stack with the founding software engineer and the wider team.
Where you land depends on you and on what we need next. Any of these could be yours:
Data infrastructure and the data model underpinning how we ingest, process and output data
APIs and services that other systems and agents plug into
Workflow orchestration and the systems that track what the lab is doing in real time
Pipelines that structure incoming data, with audit logging so nothing is unaccounted for
The platform underneath it all: data-serving abstractions, auth and access control, and observability
Whatever you own, you own it end to end. You will write production code from your first weeks, help set the architecture and the engineering culture, and work closely with scientists and with the team that learns from the data we produce.
Your first 90 days
FIRST 30 DAYS
Get productive in the codebase and ship your first change, following the team's review and deployment practices.
Take ownership of a service or surface within the team.
DAYS 30 TO 60
Ship a meaningful slice of your surface into use, in the hands of the scientists who depend on it.
Wire your work into the shared data model so everything it touches is captured and traceable.
DAYS 60 TO 90
Own your surface end to end, including its reliability, observability and on-call.
Help shape the architecture and the next hires as the team scales.
Who you are
You are a generalist who has shipped production systems that other people depend on. You write good code at speed, you have opinions about architecture, and you have learned when to hold them and when to defer. You are happy owning a service end to end, including the parts that are not glamorous. You have worked across the stack and can pick up whatever the problem in front of you needs.
You do not need a biology background and we will not test for one; the science is something you will learn by working next to it. What we do want is curiosity about what this infrastructure makes possible, and what it means for the people who will use it.
MUST HAVE
Bar-raising. You strive for excellence, raise the bar wherever you land, and hold it when it would be easier not to. We care about the finest details in our processes and our software, and you should want to.
Speed. Comfortable with ambiguity, with a bias towards action, learning and iterating. You can decide on partial information and revisit when better information arrives.
Big-picture thinking. There is a voice in your head asking why you are building this, who it is for, and what would make it 100x better.
Range. A generalist: backend services and APIs, data pipelines, and front-end to ship a usable interface. Fluent in at least one language you build production services in, and happy to work in whatever stack the team settles on.
AI-native building. You build with coding agents by default, and you have opinions and taste about what they produce rather than blind faith in the output.
Engineering discipline. Rigorous CI/CD and automated testing are how you work, not something you bolt on later.
End-to-end ownership. Architecture, reliability, observability and the on-call pager, including the parts that are not glamorous.
NICE TO HAVE
Experience at the software-to-physical-world boundary (lab automation, robotics, manufacturing, logistics, scientific instruments, or energy).
Orchestration, scheduling or workflow-engine work, and distributed systems at scale.
Data-intensive systems: pipelines, ontologies or knowledge graphs, provenance or lineage.
Early-stage or founding-engineer experience at a venture-backed company.
Why this is unusual
Most software roles like this build a product that lives entirely on a screen. This one connects to the physical world. The software you build drives real experiments, and the data it captures is the product, not telemetry about it. When something deviates, your software is what catches it and records why.
You will also work at the same table as software, hardware and biology, and the three do not always agree. Some engineers find that mix energising; some find it distracting. It is worth knowing in advance which one you are.
How we work
You will work in a hybrid pattern with regular time in London, close to the people and the work, because the software is built close to the thing it runs. The rest of the team is distributed across several locations and works flexibly, and we keep a light shared rhythm: a Monday kickoff, a Thursday all-hands, a short daily team sync, and a quarterly offsite. We are a small team that documents in the open and backs the best idea regardless of who has it.
We look after people well. In the UK that means 30 days of annual leave plus public holidays, a pension with a 10% employer contribution, and top-tier private health cover with Bupa, with more added as the team grows.
The process
Screening, then a behavioural and cultural-fit conversation, then a technical session or work sample with the team, including time in person in London, then references.
We are an equal opportunity employer. We make hiring decisions on merit, scope-fit, and the strength of the working relationship we expect to build with each hire. Applications welcome from candidates of any background.