Senior Fullstack Engineer (up to £105k)

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The role

Most companies talk about AI. This one uses it to solve a core business problem: predicting customer churn months in advance and automating revenue retention. They're a Series A company, backed by leading investors, and are scaling their platform from dozens to hundreds of enterprise customers.

You'll join a lean, six-person engineering team, working across a modern fullstack. This isn't a role for someone who wants to just ship features; you'll own significant pieces of the data platform, from scalability and reliability to embedding AI directly into both the product and engineering workflows. Expect deep technical problems, not just application-layer tasks.

The work

• Build and scale core data platform components, moving from dozens to hundreds of enterprise customers.
• Drive robustness and reliability across the stack, from Postgres and Redshift to Apache Iceberg.
• Own infrastructure on AWS and Kubernetes, not just application code.
• Integrate AI directly into the product and engineering workflows, moving beyond experimentation.
• Reduce manual support overhead through automation and platform improvements.

What You Bring

• You have 5+ years of production experience, or equivalent depth, owning significant platform components end-to-end.
• You're proficient across a Python (Django, Flask, FastAPI) and React stack, with deep backend experience in Postgres, Apache Iceberg, or Redshift.
• You've deployed and operated services on AWS with Kubernetes and are ready for infrastructure ownership.
• You actively use AI tooling in your engineering workflow and want to build the infrastructure to embed it deeper.
• You thrive on ambiguous, technically challenging problems and can articulate your past architectural decisions.