Founding Software Engineer

The one who turns intelligence into infrastructure. Someone builds a model that says "reprice this SKU to £24.99." Someone else builds a demand forecast that says "reorder by Thursday or you're out of stock by Monday." None of it matters until it runs in production. Until it is fast, reliable, and trusted enough that people let it make decisions on its own. And none of it becomes intelligent until the system can observe what happened, learn from it, and make a better decision next time without being told. That is the difference between automation and agentic AI.

Healf is Europe's fastest-growing company. From £1m to over £100m in under three years, with a small, talent-dense team and an electric culture with day one founder intensity. Now we're aiming for £1bn in the next three. We curate the world's best wellbeing brands across The Four Pillars: EAT, MOVE, MIND, SLEEP. The next chapter is harder and more interesting. We are moving from one market to many, from e-commerce to a technology platform, and from curating wellbeing to defining it.

Healf's commercial engine runs on manual processes. Pricing changes happen in spreadsheets. Purchase orders are placed by hand. Out-of-stocks are discovered after they happen. Marketing bids are set and left. This works at one market and one speed. Project Atlas is taking the company into Germany and beyond. The complexity multiplies: different pricing dynamics, different competitive sets, different supplier economics, all moving simultaneously. Gifted analysts managing this manually in one market drown in five. The answer is not more analysts. It is agentic systems that develop their own commercial logic through continuous interaction with real markets.

A system that observes that a particular product category in Germany has different price elasticity than the UK, hypothesises a pricing strategy, tests it, measures the outcome, and updates its own model. A system that gets measurably smarter with every transaction. Healf is pre-quant. You are not building rule-based automation. You are building systems that learn. And commerce is a better domain for this than almost any other, because the feedback is fast and unambiguous.

What you will own:

• The commercial decision engine. Production infrastructure that takes pricing models, demand forecasts, and marketing intelligence and turns them into autonomous action: repricing, reordering, bid adjustment, inventory allocation.
• The integration layer. Build the pipelines, APIs, and integrations that let commercial decisions flow through the business in real time.
• The trust architecture. Autonomous commercial systems need to be trustworthy. Design that trust.
• The multi-market architecture. Everything works across markets from day one.
• The learning loops. Work directly with the Founding Data Scientist to put models into production and close the feedback cycle.

What you will have built in a year:

• At least one commercial decision fully automated in production, learning from outcomes, measurably better than the manual process.
• A system architecture designed for multiple markets from the start.
• Trust infrastructure that makes the commercial team comfortable letting the system run autonomously.
• Data pipelines feeding commercial models with clean, real-time data from every relevant source.
• The foundation of a commercial intelligence platform that absorbs new decision types as models are built.

Why you're Healf:

• You have built systems that make decisions in production.
• You know what it takes to make that trustworthy: monitoring, fallbacks, circuit breakers, graceful degradation.
• You think in learning loops, not just execution.
• You care about feedback cycles, outcome measurement, and the infrastructure that turns a system that acts into a system that learns.
• You think in systems.
• You are pragmatic. You build the simplest thing that works.
• You are fluent with modern AI tooling and use it aggressively.
• You care about the outcome, not the craft of the typing.
• You have come from somewhere that software makes real-time commercial decisions at scale.
• You are excited by the blank page.

Show us:

• A system you built that makes autonomous decisions in production.
• Evidence you have built systems that learn from their own outputs.
• A moment where you designed for trust.
• Proof you can move fast without moving recklessly.

The deal: Competitive base plus meaningful equity for the right person. We ask a great deal of the people who work here. We expect full ownership and a genuine commitment to give this chapter everything you have.