Software Engineer (Full Stack)

At ResultFlow.ai, we build AI that helps ecommerce stores convert more of their visitors into customers. Merchants add our JavaScript plugin to their site, and our AI runs experiments and personalises their pages automatically, carrying learnings from one store to the next. It is a genuinely hard problem that spans frontend, backend, data, and LLM systems, all running on real, live stores where correctness matters.

We are a small, fast-moving team that makes decisions with data and ships quickly. We are looking for a Software Engineer to build real features across our product and grow quickly while doing it.

This is a hands-on role for a strong generalist a few years into their career. You will own features end to end: understanding the problem, building it, deploying it, and making sure it works in production. You will work across the stack rather than in one narrow corner, and you will be given real responsibility early.

We do not expect you to have done all of this before. We expect you to be solid where you are strong, honest about where you are not, and quick to close the gap.

• Build and ship features end to end, from problem to running in production.
• Work across the stack: frontend that runs on third-party sites, backend APIs and integrations, data, and LLM-powered features.
• Deploy your own work and take responsibility for how it behaves once it is live.
• Ask the right questions before building, and clarify requirements rather than assuming.
• Learn quickly in unfamiliar areas, and dig into the fundamentals rather than skimming the surface.

• 2 to 3 years of professional software engineering experience, building software people actually used.
• Solid backend ability. Comfort in a language such as Python or Java, and experience building APIs, handling authentication, and integrating third-party services.
• Frontend competence. You understand how the browser works: rendering, the DOM, the event loop, and networking, and you can build and reason about interfaces.
• Databases and SQL. You can design a sensible schema and write real queries, and you understand why a query might be slow.
• Deployment. You have deployed and run your own work, whether on a VPS or through a cloud platform such as AWS.
• A questioning, data-driven mind. You reach for evidence rather than opinion, you ask why, and you are comfortable being wrong.
• Ownership. You follow through, communicate clearly when you are blocked, and see things to completion.
• A fast, deep learner. You pick up unfamiliar tools and domains quickly and get to real understanding.

• Experience building with LLM APIs, and an understanding of concepts like temperature, tokens, and structured output.
• Exposure to data warehouses, pipelines, or working with data at scale.
• Containers and orchestration (Docker, ECS, or Kubernetes).
• Any experience with experimentation, A/B testing, or personalisation, which is the core of what we do.
• A basic grasp of statistics, enough to reason about whether a result is real.

• You will use AI coding tools. We use them ourselves, including Claude Code, and we expect you to use them well. The one firm rule is that you understand and can explain everything you ship.
• We judge the work, not the person, and everyone from the newest joiner up is treated the same way.
• We value people who take ownership, ask when they are stuck, and follow through.