Overview

We are looking for a Full Stack Developer to build and deploy applications end to end, using AI coding tools as a core part of the daily workflow rather than an occasional aid.

Responsibilities

• Define specification formats, API contract standards, and project templates used as the starting point for new builds.
• Establish coding standards, engineering-context files, and AI-usage guidelines that keep AI-assisted output consistent and safe across projects.
• Determine where AI tools are used in the workflow (implementation, testing, documentation, review) and where manual review is required.
• Design and build full-stack applications end to end, applying established specifications, standards, and pipeline as the reference implementation.
• Design and maintain CI/CD pipelines and release strategy as a reusable capability across projects, not a one-off setup per project.
• Deploy applications to cloud and containerised environments and monitor performance after release.
• Onboard other engineers and teams onto established workflows, including walkthroughs and support during initial adoption.
• Review code from teams following the practice, including AI-generated code, applying consistent quality standards.
• Incorporate delivery outcomes and feedback from adopting teams to refine templates, guidelines, and pipelines on an ongoing basis.
• 3-6 years of hands-on experience building and shipping full-stack applications in production.
• Strong hands-on experience with React.js or Angular on the frontend, and Node.js and/or Python on the backend.

Qualifications

• Solid Git workflow discipline and experience working from written specifications rather than verbal requirements.
• Working knowledge of relational databases (MySQL/PostgreSQL) and familiarity with NoSQL databases.
• Understanding of authentication mechanisms such as JWT and OAuth.
• Hands-on, daily experience using AI coding assistants such as GitHub Copilot, Cursor, Claude Code, ChatGPT, or similar tools for writing, reviewing, and debugging code.
• Working knowledge of more than one AI tool or model, and the judgment to choose the right one for a given task rather than defaulting to a single tool.
• Practical experience using AI tools beyond code generation - for testing, documentation, code review, and troubleshooting.
• Ability to write clear, effective prompts and instructions to get accurate, usable output from AI tools, and to catch and correct AI mistakes.
• A genuine, active interest in keeping up with new AI tools, models, and techniques as they evolve.
• Strong written and spoken communication skills in English
• Strong interpretation skills: the ability to read a specification, ticket, or instruction carefully and understand exactly what is being asked, asking clarifying questions when something is unclear.
• Ability to clearly explain technical decisions and AI-assisted work to both technical and non-technical stakeholders.
• Exposure to Kubernetes or other container orchestration beyond basic Docker usage.
• Familiarity with observability tooling such as Sentry, Prometheus, or Grafana.

Education

• Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent hands-on experience.