Tech Lead in Wilmslow

This is a real opportunity to shape how a squad builds and delivers software, at a moment when that direction is yours to influence. You will have genuine input into the technical approach, the team culture, and the outcomes, with the support of Engineering Managers and coaches around you. We are restructuring how we build and own software. That means moving from a traditional release cycle to CI/CD, decomposing shared services into team‑owned boundaries, and shifting the squad towards a genuine DevOps model. AI is central to how we work, not as a layer on top but embedded in how the team thinks, builds, and delivers. The goal is a truly autonomous team: one that owns its own systems, sets its own pace, and uses AI as a natural part of how it operates.

Key Responsibilities

• Platform Transformation and Modernisation: Lead the technical execution of a major platform restructure. This is hands‑on architecture work, not oversight. Drive the decomposition of shared hosted services into team‑owned libraries and services, defining the boundaries, managing the risk, and delivering the change. Own the move from a traditional release process to CI/CD. Build the pipelines, establish trunk‑based development, ensure fast and reliable deployments, and make continuous delivery the norm for your squad. Work towards a DevOps model where your team owns the full lifecycle, covering infrastructure, observability, and deployment. Make pragmatic calls about technical debt in the context of active change, knowing what to tackle now and what can safely wait.
• Technical Leadership and Architecture: Make architectural decisions for your product area and own the technical direction. Design and implement complex features hands‑on. Write production code daily. Lead technical discussions and design sessions, and make the call when the team needs direction. Run technical spikes and proof‑of‑concepts to validate approaches before full implementation. Balance technical excellence with delivery pragmatism. Collaborate with architects and other Tech Leads on decisions that cut across the wider organisation.
• Code Quality and Engineering Practice: Lead by example: write clean, testable, secure code that others want to emulate, and show how AI can support that standard rather than shortcut it. Drive TDD/BDD adoption through pairing and demonstration. Use AI to accelerate this, generating test scaffolding, exploring edge cases, and helping engineers see good practice in action more quickly. Own the code review culture and provide constructive, educational feedback that raises the bar for everyone. Embed secure coding practices across the team: threat modelling, security testing, and dependency management. Build observability into your systems from the start, covering instrumentation, logging, monitoring, and alerting, so that your team always has a clear picture of what their systems are doing in production. Manage technical debt at both the code and system level, and refactor proactively.
• AI‑Native Engineering: Bring AI into how you reason about problems and design solutions, treating it as a core part of your engineering practice rather than an occasional tool. Design and build AI agents that do real work: automating repetitive engineering tasks, accelerating delivery workflows, and reducing the coordination overhead that slows teams down. Embed AI‑powered workflows into the team's delivery capability, from code generation and review through to testing, deployment, and observability, so that the team ships with greater speed and confidence. Help your engineers develop real AI fluency, including how to frame problems well, how to verify outputs critically, and how to build systems where AI agents play a meaningful role. Spot opportunities to bring AI agents and automation into the product itself, building them as well‑engineered capabilities that solve real problems for customers. Hold the bar on quality regardless of how code or workflows are produced. Speed matters, but judgement and rigour remain yours to own.
• Technical Mentorship and Team Development: Mentor through doing: pair programming, mob sessions, and live code reviews. Build the team's capability in the practices that autonomous teams need, from DevOps thinking and system ownership through to AI‑native ways of working. Grow the team's confidence to make sound technical decisions independently, with less need to rely on you over time. Create a safe environment for technical experimentation and learning from failures. Contribute to technical interviews and the onboarding of new engineers.
• Delivery: Break down complex features and transformation workstreams into shippable increments that deliver value early. Provide realistic technical estimates and flag risks and dependencies before they become blockers. Work with your Product Owner on technical feasibility and implementation approach. Keep your Engineering Manager informed on technical blockers, risks, and progress. Participate in agile ceremonies: planning, refinement, stand‑ups, reviews, and retrospectives.

Required Experience and Skills

• Technical: Significant experience as a senior engineer with a track record of technical leadership on complex, evolving systems. Deep expertise in at least one backend stack, with the ability to work across multiple languages and frameworks. Strong full‑stack capability across backend, front‑end, databases, and cloud infrastructure. Practical knowledge of cloud platforms (Azure/AWS) and containers (Docker/Kubernetes). Strong security fundamentals across OWASP, secure coding, threat modelling, and security testing. Proven ability to design scalable, maintainable architectures and evolve complex legacy systems.
• AI‑Native Engineering Practice: Demonstrable experience using AI natively across your engineering work, including designing and building agents or automated workflows rather than simply using AI‑assisted tooling. Experience introducing AI into team practice in a way that reinforces quality and craft, not one that trades them away for speed.
• Behavioural: Technical credibility: engineers respect your judgement and look to you for direction. Clear communicator: able to explain complex concepts to engineers, Product, and stakeholders. Pragmatic decision‑maker: able to balance competing priorities, reach a conclusion, and move forward. Comfortable working through ambiguity and helping a team stay focused when things are not fully defined. Strong sense of ownership: you take responsibility for outcomes, not just tasks, and you care when something is not right. Collaborative by nature: works well with Product, Design, other Tech Leads, architects, and coaches. Committed to continuous learning: stays current with technology, experiments, and shares what they find.

Nice to Have

• Experience in B2B SaaS or Citation domains such as HR, Health and Safety, Compliance, Certification, or eLearning.
• Experience integrating AI/ML services or LLM APIs into production systems.
• Contributions to open source or active participation in technical communities.
• Experience with event‑driven architectures, message queues, or reactive systems.
• Experience leading a team through a significant shift in engineering practice, rather than inheriting a stable, established org.