Full Stack Engineer
Senior full stack engineer (hired via RemoteStar) for a FTSE 250 fintech client, building internal AI-enablement tooling — AI-assisted coding, testing, deployment and defect triage wired into Jira, GitLab and CI/CD. Hands-on Java backend with React/React Native, TDD and pair programming; hybrid, 2-3 days in the London office.
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Fullstack
- Posted
Skills
Must have
- Extensive background as a Software Engineer with demonstrated technical judgement on production systems
- Strong in front end React / React Native or hands-on expertise in Java or a comparable backend ecosystem, working across the stack
- Strong fluency in test-driven development and pair programming as working disciplines
- Ownership experience: designed, built, deployed, and supported features or systems in production
- Genuine appetite for aggressive automation of manual steps
- Some experience evaluating or using LLM-based developer tools in a real engineering environment
Full description
At RemoteStar, we’re hiring for one of our clients - a FTSE 250 global fintech company.
Job title
Senior Full Stack Engineer - (AI enablement) Lifecycle
Location: London
Work Mode: Hybrid (2/3 days from the office)
Key Skills
Java, React / React Native, TDD, Paired Programming, AI-assisted coding
Your team:
We’re looking for a Senior Full Stack Engineer to push hard on AI across Lifecycle engineering: AI-assisted coding, testing and deployments, defect triage and observability, and the internal tooling that connects our AI tools safely to Jira, GitLab, and our CI/CD pipeline. This is a hands-on role on our Java backend. You’ll build tooling yourself, and you’ll help set how your team adopts it.
Your role in the Team’s Success:
This role suits engineers with a strong grounding in software engineering practice: test-driven development, pair programming, and real ownership of systems from design through to production support, with real depth in Java and the modern backend services ecosystem. The fundamentals matter most: engineers who can write their own tests, review their own designs, and catch their own defects, and who use AI to extend that practice further and faster. Growing into the person the whole group comes to for technical judgement is part of the role.
What you’ll do:
- Build and maintain internal tooling that embeds AI into day-to-day engineering work: coding assistants, AI-assisted test generation, deployments, and defect triage.
- Contribute to observability in the AI-assisted pipeline, so every stage shows what the tooling is doing, catching, and missing.
- Identify manual steps in coding, testing, and release that can run largely unattended, and help build the automation to get there.
- Split work into small, releasable pieces that ship continuously.
- Work closely with a product person on your product domain, so what you build is grounded in real delivery.
- Treat improving ways of working and driving AI adoption as a fundamental, ongoing part of delivering value.
- Work with the test and PM function to bring AI into the testing pipeline: exploratory test generation, defect clustering, flaky-test detection, and smarter prioritisation of what to test.
- Evaluate and help roll out LLM-based developer tools, for example Claude Code and similar, integrating them safely with our Jira, Confluence, and GitLab environments.
- Follow and help refine standards for responsible AI use in the SDLC: data handling, prompt hygiene, and guardrails around production and customer data.
- Mentor less experienced engineers on effective use of AI tooling.
- Work with security and compliance to make sure AI tooling meets our regulatory and data‑handling requirements.