Founding Software Engineer

The opportunity Substrate is building a network of fully autonomous wet labs, cloud-based data production facilities for AI biology, integrated with foundation models to become the critical infrastructure layer for AI-driven biological discovery. Our first node opens in King’s Cross, London, with several integrated workcells and two scientific verticals online by mid‑2027. Our customers range from foundation model labs to global pharma. We are hiring a founding software engineer to lead the team that builds Substrate’s operational software, the system that turns scientific intent into executed lab work, captures every run as structured data, and routes that data back to model training, customer pipelines, and Substrate’s own data factory. This is a player‑coach role.

You will write the first production code for the orchestrator, the customer interface, and the resource management layer, and you will recruit and lead the engineers who come after.

About Substrate: Substrate is spinning out of Automata, the UK lab automation company that has built the workcell platform our labs run on. Our four co‑founders are Mostafa ElSayed (CEO and founder of Automata), Oli Hoy (formerly VP Customer Experience at Automata), Alexey Morgunov (AI Scientist co‑founder, leading the Intelligence Software product), and a Founding Biology Lead joining shortly. We are aiming to have ramped up to 32 people by the end of Q1 2027. We are funded in parallel by a combination of venture funding and government grants. We are not a cloud lab, and we are not a CRO. We are an autonomous lab platform with closed‑loop integration available as one operating mode for foundation model partners.

The role: You will own the operational software product end to end. The product has five surfaces. The loop orchestrator is the heart of it: two agentic translation layers that convert scientific intent (model output, natural language, or structured input) into executable, automated workflows, and convert workflow outputs and run metadata back into destination‑specific formats for delivery to foundation models, LIMS, customer data lakes, and ELNs. Resource management will track consumables, reagents, and labware, and maintain a live representation of the physical lab so that physical inputs can be mapped onto workflow outputs. The customer interface is API‑first with a web front end. The workflow orchestrator sits above Automata’s LINQ scheduler and manages capacity allocation across customers, verticals, and device groups. The pricing and forecast engine calculates predicted and actual platform inputs and translates them into customer cost.

You will write the first production code, set the architecture, set the engineering culture, and grow the team. You will have the opportunity to build a team and help set the culture within the company. You will work closely with Alexey on the boundary between our operational software and our intelligence software (the AI Scientist and AI Assays products), and with the founding biology team on the orchestrator behaviour on the lab side.

What you will do in your first twelve months:

• PHASE 0: NOW TO AUG 2026 - Land in the team. Lock the architecture for the orchestrator and the customer interface. Decide the build vs buy boundary against LINQ. Ship the first end to end thin slice: a simple workflow submitted via the customer API, executable on a workcell, with run metadata captured and returned. Set the engineering culture: code review, deployment, on‑call, observability. Pick the languages, frameworks, and tooling we will live with.
• PHASE 1: SEP TO DEC 2026 - Stand up the resource management and digital twin services. Wire them into the protein engineering workflows being onboarded by the founding biology team. Hire the first software engineer alongside you. Define the role, run the process, close the offer. Ship the first version of the pricing and forecast engine. Connect it to the customer interface so that customers see predicted cost before they submit.
• PHASE 2: JAN TO MAR 2027 - Ramp up hiring. Move from solo building to leading a larger team. Bring the workflow orchestrator above LINQ into production. Manage capacity allocation across the protein engineering vertical and the early functional genomics work. Harden the loop orchestrator for the closed‑loop foundation model partners coming online from mid‑2027.

Who you are: You are an experienced software engineer who has shipped production systems at depth. You have led a small team or are ready to. You write good code at speed, you have strong opinions about architecture, and you have learned (often the hard way) when to defer those opinions. You have worked at the boundary where software meets physical reality (lab automation, robotics, manufacturing, logistics, scientific instruments, energy) and you understand that the interesting failure modes live there. You are excited by the prospect of writing the first lines of code for a system that will run a real lab. You are pragmatic about agentic systems and foundation models; you have used them in production rather than read about them in posts. You want a player‑coach role specifically. You enjoy interviewing, hiring, mentoring, and building culture, and you do not want to be only an individual contributor or only a manager. You care deeply about building a world‑class team. You are comfortable with early‑stage ambiguity, with making decisions on partial information, and with revisiting them when better information arrives.

MUST HAVE: Five or more years of professional software engineering experience, with at least one leading or co‑leading a small team. Production experience with backend systems, distributed services, and either workflow orchestration or scheduling systems. Strong working comfort with at least Python, and willingness to learn the necessary tools. Track record of designing APIs that other engineers have actually used. Direct experience of the software‑to‑hardware boundary, in lab automation, robotics, manufacturing, or an analogous domain.

NICE TO HAVE: Experience of an early‑stage founding‑engineer role at a venture‑backed company. Familiarity with foundation model APIs, agentic patterns, and the practical realities of putting them in production. Background in or near scientific computing, bioinformatics, or LIMS / ELN systems.

Why this is unusual: Most software engineering roles at venture‑backed companies are either a pure software product or a thin software layer on top of someone else’s infrastructure. This is neither. You will be writing the software that decides what physical experiments run, when, on which workcell, with which reagents, for which customer, and you will be doing that inside a wet lab business with biology and engineering colleagues at the same table. Operational software is also one of three product surfaces being built simultaneously. Alexey is leading the efforts on intelligence software (the AI Scientist and AI Assays products). The biology team is building the assay portfolio. Your work has to integrate cleanly with both, and you will spend real time at the boundary. Some engineers find this energising; some find it distracting. Worth knowing in advance which one you are.

Compensation and equity: We pay competitively against the London market for senior software engineers at venture‑backed companies, calibrated to seniority and to the specific scope of this role. We will discuss numbers with serious candidates after first conversations. Equity is meaningful, with vesting on the standard four‑year schedule and a one‑year cliff. We can talk through the philosophy and the maths in detail when we meet.

How we work: Working pattern is open. We will design around the strongest candidate, with a bias towards willingness to spend some in‑person time at our King’s Cross site, particularly during the early phases while the team is forming and the architecture is being set. Most of the founding team are in the office most days. 30 days annual leave. A learning budget you can use for conferences, courses, books, and time. The founding team operates on a weekly cadence with a Monday planning meeting and a Friday close, and a quarterly off‑site. We are direct with each other, we write things down, and we expect to be challenged.

The team you will join: You will report to Oli Hoy, co‑founder, who leads our autonomous lab build‑out and is also responsible for the broader operations of the company. You will work most closely with Alexey Morgunov on the intelligence software boundary, and with the founding biology team on the orchestrator behaviour at the lab side.

How to apply: Apply via Ashby with whatever you think shows your work best: a CV, a short email, links to GitHub or to systems you have built, a piece of writing you are proud of. We read everything that comes in. Our process is four stages. An initial conversation with Oli to understand what you want from the role and what we want from it. Two technical sessions with our external technical advisor: an architecture deep‑dive on how you would build the operational software, and a session on how you would build and lead the engineering team. Finally, an in‑person founder‑team session covering scope, terms, and any final questions. We aim to move fast on candidates we are excited about; expect roughly two to three weeks end to end. If you are not sure whether you are a fit, send a note anyway. The most useful conversations we have had so far have been with people who were not sure. Substrate is 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.