Full Stack Engineer

About the role

Our client builds drugs for patient populations that traditional generic development doesn't reach, not more of the same generic drugs. To do it, their pharma, ML and data scientists rely on a mix of LLM-based applications and standard full stack software. They build this software in-house. Engineers work directly alongside the scientists using it, turning their sharpest and most ambiguous questions into shipped features, not into a support ticket for someone else's platform.

What you'll do

• Own applications end to end. Get up to speed across their mix of LLM-based and standard full stack applications, then take ownership of a growing share of them. As you take on more, you'll be designing and building features end to end rather than working one corner of a single product.
• Turn scientists' questions into shipped software. You'll work day to day with pharma, ML and data scientists, and with a few other engineers on the team. Take a rough idea of what a scientist needs, spec it out into concrete requirements yourself, then build it. There's no separate product function doing that translation for you.
• Move fast with unclear inputs. This is a high-velocity, low-structure job: expect a constant stream of unstructured feedback and the need to turn it into shipped, working software, not a fully-scoped ticket.
• Build the agents, not just use them. Build and evaluate agentic and multi-agent systems as a core part of the job. This isn't a side project or an experiment, it's part of the core application set scientists rely on day to day.
• Grow by taking on more. Our client is a young company without a fixed playbook: the more you build, the more you can own. Progression here is driven by impact rather than tenure. One of the team's current engineers joined as an intern and now owns engineering end to end.

Who we're looking for

A full stack engineer who has taken a product from an idea to production, and who has built and shipped a real AI agent, not just experimented with one.

Core experience

• 3 to 5 years as a full stack engineer, strong in Python and TypeScript
• Has taken at least one application from zero to one (full front end and back end) through to completion
• Has built a real agentic AI application and can talk about how its impact was measured, not just that it was built
• Comfortable deploying on Google Cloud

Preferred background

• Pharma or biotech experience is the strongest fit
• A general research background, in any field, is a solid second
• Open to strong candidates from other backgrounds too
• Startup experience is strongly preferred over big tech

Also required

• High autonomy: comfortable owning a problem end to end with minimal hand-holding
• Comfortable with ambiguity and fast-changing priorities
• Confident coordinating directly with non-engineering stakeholders (scientists), not just other engineers