About the Role
Management Level D Job Title: AI Enabled Engineering Leader Reports To: Head of Engineering Experience: 15+ years in Software Engineering Role Overview This is a senior, hands-on engineering leadership role reporting directly to the Head of Engineering. The role defines, implements, and scales AI‑enabled engineering practices that materially improve developer experience, delivery speed, and software quality across Scrum teams. The role blends technical leadership, strategy, execution, and influence. You will work directly with teams to embed AI across the full SDLC-requirements, design, coding, testing, review, non‑functional requirements, and CI/CD-while establishing guardrails, standards, and a sustainable AI Community of Practice (CoP). This is not an advisory role. You will build, pilot, coach, and scale. Key Responsibilities 1. Strategic Partner to the Head of Engineering Act as a trusted advisor on AI adoption, developer experience, and delivery effectiveness Shape and execute engineering strategy for AI‑enabled delivery Translate strategy into practical, team‑level adoption 2. Hands‑On Enablement with Scrum Teams Work directly with teams to embed AI into day‑to‑day delivery Pair with engineers on real work: requirements, design, coding, testing, PRs, and releases Identify friction points and continuously improve tooling and practices 3. AI‑Enabled SDLC (End‑to‑End) Define and operationalize AI usage across: requirements, development, testing, review, NFRs, and CI/CD Establish clear, practical “how we build software here” standards 4. Best Practices, Standards & Guardrails Define responsible AI usage standards: validation, testing, security, documentation, traceability Produce lightweight standards, templates, prompt patterns, examples, and checklists teams use 5. Developer Experience & Tooling Embed AI tools into IDEs, PR workflows, testing, and CI/CD pipelines Improve the developer inner loop: faster feedback, reliable pipelines, reduced toil Build POCs, reference implementations, and reusable templates for GenAI and agent‑based systems Support teams moving from experimentation to production 6. Community of Practice (CoP) Leadership Create and lead an AI Engineering CoP Establish playbooks, libraries, demos, office hours, and team champions Evangelize practical GenAI and agentic AI usage Run workshops, demos, brown‑bags, and internal documentation Enable safe, pragmatic adoption without disrupting delivery 7. Measurement & Continuous Improvement Define and track metrics: cycle time, lead time, deployment frequency, defect escape rate, test effectiveness, CI/CD health, developer satisfaction Run pilots, measure outcomes, and scale what works Required Qualifications 15+ years in software engineering with strong hands‑on coding background 5+ years leading AI, productivity, platform, or enablement initiatives Recent (2–3 years) experience scaling GenAI‑assisted SDLC adoption Experience leading initiatives across multiple teams Deep understanding of SDLC, CI/CD, and quality engineering Strong influence, coaching, communication, and executive‑level presence Coding Languages & Frameworks Languages: Python, C#/.NET, JavaScript/TypeScript (Node.js), SQL, Shell AI / GenAI: PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, LlamaIndex, Vector DBs Agentic Systems: LLM agents, tool use, planning, memory, reflection, RAG, prompt engineering, guardrails Architecture: Agent orchestration, event‑driven systems, human‑in‑the‑loop workflows Testing & Quality: Agent testing, probabilistic vs deterministic testing, regression, simulation AI Ops: Monitoring, drift, cost, CI/CD for AI systems, safe rollout and rollback Cloud: AWS or Azure AI services Preferred Qualifications Experience improving developer productivity at scale Modern CI/CD and test automation modernization Building and sustaining Communities of Practice Exposure to security, reliability, and observability standards What Success Looks Like (6–12 Months) AI‑enabled practices adopted across most Scrum teams Measurable improvements in speed, quality, and predictability Reduced CI/CD and development friction A thriving, self‑sustaining AI CoP Clear executive visibility into outcomes Why This Role Matters This role ensures AI adoption is practical, responsible, and impactful shaping how software is built and improving outcomes for engineers, the business, and customers. We are committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships. Please note any offer of employment is subject to satisfactory pre-employment screening checks. Our people and platforms connect businesses with markets, engage customers with their investments and allow organisations to grow and transform. Our vision is to help businesses and individuals succeed, creating positive experiences for the millions of people who rely on us for a sustainable future. We provide share registration, deliver services for reward and benefits and develop solutions for customer management in regulated industries. Our work with some of the most significant organisations in the UK and US means we engage with 29 million of their shareholders, pensioners and employees.