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EngineerFull-timeSenior Level

Technical Solutions Delivery Manager - AI

UK / Europe (EMEA)Competitive Salary

We are seeking a Technical Solutions Delivery Manager 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.

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 reviews

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 organisations
  • 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)

Nice to Have

  • 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 AutoGen

Benefits & Perks

Opportunity to work on a globally recognised consumer brand
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

Apply Now

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