AI Solutions & Delivery Manager

About IMD

The International Institute for Management Development (IMD) has been pioneering
leadership development for nearly 80 years. Founded by business for business, we are an
independent university institute with Swiss roots and global reach. Operating from
Lausanne with strategic hubs in Singapore, Shenzhen, and Cape Town, IMD works with
20,000+ executives from 120+ countries annually. Our 145,000+ alumni form a powerful
global network. Consistently ranked among the world's top business schools, IMD bridges
cutting-edge research with real-world application to help leaders solve problems, scale
solutions, and drive impact. Real Learning for Real Impact.

To reinforce our team, we are looking for a

AI Solutions & Delivery Manager

The Job's Mission

Leads the design and delivery of AI-enabled solutions across IMD; today generative and agentic AI, tomorrow whatever comes next. The role treats AI as an engine that amplifies IMD's human expertise and institutional impact, never as a replacement for it. It translates business opportunities into secure, scalable, cost-effective, and ethically governed solutions that strengthen productivity, decision-making, and service quality.
Working across IMD's business units and with IT, data, security, legal, and external partners, the AI Solutions & Delivery Manager leads IMD's AI Advanced team, drives the agentic AI transformation, and builds the institutional capability to adapt as the technology landscape evolves.

Key Activities & Accountabilities

AI Solutions, Transformation & Adoption
•    Partner deeply with business units to understand their intricacies, from strategic objectives to cross-team interdependencies, identifying where AI can enable innovation, creativity, and productivity.
•    Identify, shape, and deliver high-value AI use cases across business units: machine learning, assistants, automation flows, agentic solutions, and emerging paradigms as they mature.
•    Apply product management discipline: define clear problem statements, success metrics, roadmaps, and prioritization frameworks so AI initiatives are run and measured as products, not one-off projects
•    Apply systems thinking, see how a use case ripples across processes, teams, data, and existing tools before committing to build it, and design for the whole system rather than the isolated task
•    Apply design and critical thinking: use design thinking and UX / customer-centricity to ensure solutions are intuitive, genuinely adopted, and solve the user's real problem
•    Translate business needs into solution designs, adoption plans, success measures, and operating models, keeping people at the center of every workflow.
•    Design agentic workflows where AI supports tasks, triggers actions, and coordinates across systems, always with meaningful human oversight and clear accountability.
•    Assess feasibility, value, cost, data readiness, and risk before moving AI ideas into delivery.
•    Scan the horizon continuously, translating fast-moving AI developments into practical, durable opportunities for IMD.

Architecture, Delivery & Cost Stewardship
•    Lead the delivery lifecycle end to end: intake, prioritization, design, development, testing, release, support, and continuous improvement, in line with IMD’s PMO practices.
•    Architect solutions deliberately with IT, architecture, data, security, and vendors, so they are scalable, integrated, maintainable, secure, and built to evolve.
•    Define reusable technical patterns: enterprise integrations, data sources, APIs, identity, permissions, monitoring, and support models.
•    Own the cost dimension of AI: forecast, monitor, and optimize consumption and licensing so value demonstrably exceeds spend.
•    Make deliberate build-vs-buy calls for each opportunity, weighing vendor and platform solutions (e.g. Microsoft 365 Copilot, Azure AI Foundry) against custom build, and own the resulting AI tool and vendor portfolio, including licensing and contracts.
•    Prune and consolidate proactively: retire pilots that didn't deliver, merge overlapping tools and duplicated capabilities, and simplify IMD's AI landscape to cut cost and complexity — treating this as a core, ongoing accountability alongside building new solutions.
•    Negotiate and manage vendor relationships as part of the broader technology portfolio, in partnership with IT and procurement.

Responsible AI, Governance & Risk
•    Embed responsible AI principles, including fairness, transparency, privacy, sustainability and human dignity, across design, delivery, adoption, and monitoring.
•    Ensure AI and agentic solutions include guardrails, human approval points, explainability, documentation, and auditability.
•    Partner with legal, security, compliance, and data governance on privacy, risk, and institutional requirements.
•    Support AI governance through use case assessment, value tracking, cost oversight, and post-release monitoring.

Stakeholder Partnership
•    Act as a trusted partner across business units, helping colleagues identify opportunities, clarify needs, and adopt AI responsibly and confidently.
•    Facilitate workshops to define problems, align expectations, validate options, and build genuine commitment.
•    Communicate progress, risks, trade-offs, and recommendations clearly to technical and non-technical audiences alike.
•    Coordinate internal teams and external partners to deliver coherent, high-quality solutions.

Team Leadership & Capability Building
•    Lead, coach, and develop team members working on AI, automation, analytics, and technology delivery.
•    Manage team priorities, capacity, and skills development across current and future initiatives.
•    Foster a culture of curiosity, experimentation, responsibility, and continuous learning — so the team grows with the technology, not behind it.
•    Build knowledge-sharing practices that keep IMD current as AI methods and standards evolve.

Education

•    Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, Business Technology, or a related field. Alternatively, over 10 years working in the Data Science / Technology field
•    Certification or training in AI, cloud, agile delivery, product/project management, or change management is a plus.

Experience

•    Experience as a people leader
•    Proven experience delivering AI, automation, or enterprise technology solutions.
•    Solid understanding of generative and agentic AI, adoption practices, responsible AI, and AI cost management.
•    Experience leading technical or cross-functional delivery teams.
•    Strong working knowledge of IT delivery, APIs and integrations, cloud platforms, security, testing, release management, and support models.
•    Experience partnering with stakeholders to define needs, prioritize, manage expectations, and drive adoption.

Competencies

•    AI-fluent and future-oriented, with sound judgment on practical value, feasibility, cost, and risk. Comfortable navigating a field that reinvents itself yearly.
•    Structured and delivery-minded, bringing clarity, pace, and discipline to complex topics.
•    Trusted stakeholder partner, able to challenge constructively and influence adoption across business units.
•    People-focused leader who coaches, empowers, and raises team maturity.
•    Ethically grounded and pragmatic, with strong judgment on security, privacy, sustainability, and the human impact of technology.

How to apply

If you have the above skills and would like to work in our stimulating environment, please send your complete application file (letter of motivation and resume in English, copies of your work certificates and diplomas). 

If you’re a qualified candidate with a disability (such as dyslexia, sight and/or hearing disabilities, etc) and you need a reasonable accommodation in order to apply for this position, please specify it in your application. 

A valid Swiss work permit or Swiss or EU-25EFTA citizenship is required for this position.