Ofertas › Tech4 Ltd
Tech4 Ltd · St Paul's, United Kingdom · £80,000 - 110,000 per year
Salary: £80,000 - 110,000 per year Requirements: Deep experience building scalable, secure, cloud-based systems Proven ability to work across both legacy and greenfield codebases Strong system design fundamentals across scalability, performance, and distributed systems, including API design (REST, GraphQL) Hands-on experience with observability tooling (Datadog, Grafana, or similar) and a data-informed approach to system health and reliability Solid SQL and data management skills, with an appreciation for AI-enabled, data-driven systems Familiarity with CI/CD, containerisation (GitHub Actions, GitLab CI, Docker), and DevSecOps practices in modern AI development environments A pragmatic approach to testing, knowing what to cover, what to skip, and how to use AI to improve efficiency Experience mentoring engineers and supporting the adoption of modern tools and AI-native workflows Strong communication skills and the ability to articulate technical decisions and trade-offs clearly Responsibilities: Help the team move faster by adopting AI-native workflows and the shift to an agentic development lifecycle, without compromising the architectural qualities that make our platform reliable, scalable, and maintainable over the long term Define guardrails, review practices, and validation gates that hold AI-generated code to our standards for security, reliability, and cost-efficiency (FinOps) Design, build, and operate software across our platform, applying the same rigour to AI-augmented work as to anything else you ship Embed deeply with Product and Design from the earliest stages of discovery, using rapid prototyping and iteration to compress the gap between idea and validated solution Act as feature lead on a rotating basis, taking accountability for the development and delivery of a feature from shaping through to production Shape platform architecture with an architectural lens, contributing to long-term decisions about how AI tooling, LLM integrations, and human-in-the-loop controls evolve across the stack Continuously identify and exploit opportunities to improve performance, reliability, and user experience, using observability and analysis to find signals in noisy systems Navigate confidently across legacy and greenfield contexts, applying AI tooling pragmatically to modernise where it matters most Set the engineering standard, demonstrating through your own work what excellent looks like when much of the code is AI-generated Grow the teams capability an