At a Glance
- Tasks: Lead AI strategy and solution architecture for enterprise clients in a dynamic tech environment.
- Company: Join a globally recognised brand with an AI-first engineering culture.
- Benefits: Competitive pay, flexible work, AI training, and career progression opportunities.
- Other info: Collaborative team across multiple geographies with a focus on innovation.
- Why this job: Shape the future of AI delivery while working with cutting-edge technologies.
- Qualifications: Proven AI strategy experience and strong technical skills in mobile and cloud architecture.
The predicted salary is between 80000 - 100000 € per year.
We 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 reviews.
- [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).
- 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.
- 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.
Technical Solutions Delivery Manager– AI employer: MSE Technology
Join a forward-thinking company that champions an AI-first engineering culture, offering you the chance to lead transformative projects for a globally recognised consumer brand across 12+ markets. With a strong emphasis on continuous learning and collaboration, you'll benefit from competitive compensation, flexible working arrangements, and access to cutting-edge AI tools and training opportunities, all while mentoring the next generation of engineering leaders.
StudySmarter Expert Advice🤫
We think this is how you could land Technical Solutions Delivery Manager– AI
✨Tip Number 1
Network like a pro! Reach out to industry contacts on LinkedIn or attend relevant meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising your pitch. We recommend you rehearse how you’d explain your AI strategies and technical expertise. The more confident you are, the better you’ll connect with the interviewers.
✨Tip Number 3
Showcase your skills through real-world examples. When discussing your experience, we suggest using specific projects where you’ve implemented AI solutions. This will make your application stand out and demonstrate your hands-on expertise.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Technical Solutions Delivery Manager– AI
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI strategies and solution architecture. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant achievements!
Showcase Your Technical Expertise:When detailing your experience, focus on specific projects where you’ve defined and executed AI strategies. Use clear examples that demonstrate your hands-on experience with Agentic AI tools and how they’ve improved efficiency in your previous roles.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and how you can contribute to our AI-first culture.
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at MSE Technology
✨Know Your AI Tools
Make sure you’re well-versed in the Agentic AI tools mentioned in the job description. Be ready to share specific examples of how you've used these tools to improve efficiency in your previous roles. This will show that you not only understand the technology but can also apply it effectively.
✨Master the Architecture
Brush up on your knowledge of mobile application architecture and cloud-native patterns. Be prepared to discuss your experience with iOS, Android, and cross-platform frameworks like Flutter or React Native. You might even want to sketch out a reference architecture during the interview to demonstrate your hands-on expertise.
✨Showcase Your Strategic Mindset
Since this role involves defining and executing AI strategies, come prepared with a few case studies from your past experiences. Highlight how you conducted gap analyses, prioritised use cases, and developed phased implementation roadmaps. This will illustrate your ability to think strategically while also being hands-on.
✨Engage with C-Suite Scenarios
Practice presenting complex technical concepts in a way that resonates with non-technical stakeholders. You may be asked to explain your solutions to C-suite executives, so focus on how your technical decisions align with business objectives. This will demonstrate your ability to bridge the gap between tech and business.
