Job Title

About the RoleWe are seeking a Technical Solutions Delivery Manager– AI with deep technical expertise and a proven track record of defining and executing AI strategy within large-scale technology delivery programmes. This is a senior leadership role bridging strategic AI vision with hands-on solutioning – you will own the end-to-end solution architecture, lead technical presales and discovery, and shape the AI transformation roadmap for enterprise clients.The ideal candidate has personally created AI strategies in previous organisations – from gap analysis and use-case identification through to phased implementation roadmaps, governance frameworks, and value realisation tracking. You are equally comfortable presenting to C-suite executives and whiteboarding architecture with engineers.You will operate across client-facing and internal contexts: leading solution design for new engagements, defining reference architectures, mentoring engineering leads, and championing an Agentic AI-first delivery culture across the organisation.Core Responsibilities• Own end-to-end solution architecture for complex, multi-market mobile and digital loyalty platforms, ensuring alignment with client business objectives and technical constraints• Define and drive AI strategy across the SDLC – identifying automation opportunities, building use-case roadmaps aligned to PI cadence (e.g., AMJ, JAS, OND), and establishing governance for AI adoption• Lead technical discovery, presales, and solutioning activities with enterprise clients, translating business challenges into structured delivery proposals• Design reference architectures for mobile (iOS, Android, Flutter, React Native), backend (.NET, Node.js), cloud (Azure AKS, Web Apps), and AI agent integration (LangChain, CrewAI, Claude)• Conduct solution reviews, architecture governance, and technical risk assessments across delivery squads• Mentor and coach Engineering Leads and Senior Engineers on architecture best practices, AI tool adoption, and technical decision-making• Define non-functional requirements (performance, scalability, security, accessibility) and ensure they are embedded in delivery from sprint zero• Represent the engineering function in programme-level steering committees, PI planning events, and client-facing reviewsAI Proficiency Requirements• [MANDATORY] Hands-on experience with Agentic AI tools or advanced AI-assisted workflows (e.g., AI-driven code generation, autonomous testing agents, AI-powered architecture review, Claude, Cursor, Copilot Workspace) that have demonstrably improved personal or team efficiency by 150–200%. Candidates must demonstrate specific examples during the interview process• Proven experience defining and executing AI strategy at an organisational or programme level – including gap analysis, use-case prioritisation, phased roadmaps, governance frameworks, and ROI tracking• Experience embedding AI agents across SDLC processes: requirements decomposition, design-to-code pipelines, automated test generation, intelligent deployment, and monitoring• Deep understanding of LLM capabilities, prompt engineering, RAG pipelines, and AI agent orchestration patterns (tool use, multi-step reasoning, autonomous task completion)• Ability to build AI maturity assessments and capability roadmaps for engineering organisationsTechnical Requirements• Extensive experience architecting mobile applications at enterprise scale across iOS, Android, and cross-platform frameworks (Flutter / React Native)• Strong understanding of cloud-native architecture patterns (microservices, event-driven, serverless) on Azure or equivalent platforms• Experience with enterprise loyalty, rewards, or commerce platforms serving multiple markets with configuration-driven personalisation• Deep knowledge of CI/CD, automated testing strategies, security tooling, and DevOps best practices• Experience with technical presales, RFP responses, estimation, and solution proposal development• Proficiency with Jira, Confluence, and programme-level delivery artefacts within PI planning frameworks (SAFe or equivalent)Desirable Skills• Experience with Server-Driven UI (SDUI) patterns and multi-market configuration management architectures• Background in building or scaling engineering consultancies / capability practices• Published thought leadership, conference talks, or internal whitepapers on AI in engineering delivery• Familiarity with Azure AI services (OpenAI, Cognitive Services, ML Studio) or equivalent• Experience with AI-focused frameworks: LangChain, LangGraph, CrewAI, Semantic Kernel, or AutoGenWhat We Offer• Opportunity to work on a globally recognised consumer brand across 12+ markets• An AI-first engineering culture that invests in cutting-edge tools and continuous learning• Collaborative, distributed team environment spanning multiple geographies• Competitive compensation package with performance-based progression• Access to AI training, certifications, conference attendance, and dedicated innovation time• Flexible working arrangements with a focus on outcomes over hours