AI-First Tech Lead: Hands-On Engineering & Team Growth

A senior engineering leader who is responsible for the technical health, delivery performance, and professional development of their team. The Tech Lead is the primary engineering owner for one or more teams - setting technical direction, building culture, and bridging the gap between engineering and the broader organisation. Tech Leads are expected to actively drive AI-native culture within their team and model best practice for everyone they manage.

The step from Technical Project Lead to Tech Lead is the most significant transition in the engineering career path. The TPL role is delivery-focused; the Tech Lead role adds sustained people leadership, team design, and function-level accountability. You are no longer primarily measured by what you build or what your project delivers - you are measured by the health and capability of your team over time. This means investing in people who may not yet be performing, having difficult conversations, and sometimes slowing down delivery to get the team architecture right. It is a fundamentally different role, and the instincts that made you a great TPL will need to evolve. Hands on contribution remains significant. Approximately 60% of time is spent on direct technical work - coding, design, review, and architectural decision making - and 40% on line management, stakeholder communication, hiring, and engineering strategy.

Responsibilities

• Own the technical health of one or more delivery teams: architecture, standards, quality, and culture.
• Line manage up to 6 engineers directly or up to 10 indirectly, including regular 1:1s, objective setting, development support, and performance management.
• Make or delegate architectural decisions with confidence, maintaining long term codebase coherence.
• Balance hands on technical contribution with management and leadership responsibilities.
• Drive quality and delivery standards across the team, setting clear expectations and holding them consistently.
• Contribute to sprint planning and prioritisation alongside the Programme Manager and Analysts.
• Lead incident response for the team, ensuring post mortems produce systemic improvements and address root causes.
• Represent engineering in stakeholder conversations, communicating clearly on delivery status, technical risk, and capacity.
• Partner with the Head of Engineering on resourcing, team design, and delivery strategy.
• Contribute to hiring by defining role requirements, leading technical interviews, and making recommendations.
• Support the development of Senior Engineers towards greater leadership capability.
• Operate with commercial awareness, understanding the revenue and margin implications of technical decisions.
• Contribute to cross function engineering strategy and platform wide architectural decisions.
• Develop or contribute to the Ignite repeatability and AI native agenda.
• Contribute to hiring strategy and team design conversations with the Head of Engineering.
• Carry full line management responsibility for direct reports, including probation management and formal performance processes.
• Support pay review and promotion recommendations to the Head of Engineering.
• Manage indirect accountability for QA leads and their reports within the Ignite structure.

AI Leadership Responsibilities

• Actively use and champion coding harnesses, building team level harnesses that standardise AI usage for common tasks.
• Understand AI agents at an implementation level, including design, risks, and appropriate usage.
• Understand and work with skills as reusable AI capabilities.
• Have a strong working knowledge of MCP (Model Context Protocol), including tool access, context management, and security implications.
• Set expectations for AI tool use within the team, defining what is encouraged, what requires review, and where human verification is required.
• Stay current with the AI tooling landscape and share relevant developments with the Head of Engineering.

Qualifications

• Languages: TypeScript and C#/.NET (sufficient depth to review and guide work in both stacks).
• Frontend: Vue.js (Customer Portal stack - review and governance level).
• Databases: SQL Server, PostgreSQL (design, performance, governance).
• Cloud & Infrastructure: Azure (architecture, cost management, security posture).
• Container Orchestration: Kubernetes (operational and governance level).
• CI/CD: GitHub Actions, GitOps (ownership and governance).
• Security: ISO 27001 controls implementation and penetration test coordination.
• Tooling: Linear, Git/GitHub, Copilot, monitoring and alerting platforms.