Capgemini is seeking a senior executive for the role of AI Engagement Manager to lead technical teams and drive AI-focused business growth. The role requires a seasoned professional to oversee the delivery of enterprise-grade AI and GenAI solutions. Responsibilities: Lead a technical team of architects, AI tech leads, and developers. Engage with clients to finalize solutions and architecture. Develop project plans and ensure successful delivery. Drive business growth with a target of 30% annual increase. Mentor team members on their career paths. Manage client relationships to ensure high NPS and secure reference customers. Requirements: 15+ years of IT experience. 5+ years of experience as an architect or AI Technical PM. Proven experience in data science (AI/ML), Agentic AI, and GenAI program management. Must have led programs with 20+ headcount delivering AI/GenAI solutions to enterprises. Experience handling client interactions and commercials. Educational qualification: B.E. degree. Professional certifications in project management are required.
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Skills for this role
Agentic AIGenerative AIData ScienceAI/MLProject ManagementSolution ArchitectureProgram ManagementClient EngagementTeam Mentoring
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A focused preparation guide, built around this job’s responsibilities and requirements.
✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01
Understand the role
What matters most
Driving 30% Annual Business Growth
The role explicitly mandates a 30% year-over-year growth target. You must demonstrate how you have previously expanded AI service portfolios within existing accounts or secured new business through strategic client engagement and solution positioning.
Enterprise-Scale AI Delivery Leadership
You are required to lead technical teams of 20+ headcount, including architects and developers. Success depends on your ability to oversee the full lifecycle of complex AI, GenAI, and Agentic AI programs while ensuring technical excellence and adherence to project plans.
Client Relationship and Commercial Management
Beyond technical delivery, you must manage client interactions and commercial negotiations. The priority is to maintain high Net Promoter Scores (NPS) and convert clients into referenceable accounts, requiring a balance of technical credibility and business acumen.
Team Mentorship and Talent Development
As a senior executive, you are responsible for the career progression of your technical team. You must be prepared to discuss your philosophy on mentoring architects and developers to ensure the team remains aligned with evolving AI industry standards.
Likely challenges to think through
Balancing Technical Depth with Commercial Targets
The challenge lies in maintaining the technical rigor required for Agentic AI and GenAI solutions while simultaneously meeting aggressive 30% growth targets. Prepare by articulating how you align technical architecture decisions with client business value to drive upsell opportunities.
Managing Large-Scale AI Program Complexity
Leading 20+ person teams in the rapidly evolving GenAI space involves high uncertainty. You may face challenges in resource allocation and technical debt management; prepare by discussing your framework for maintaining delivery excellence in high-pressure, enterprise-grade environments.
03
Practice your answers
Technical practice
Architecting Agentic AI Solutions
What to coverExplain your approach to designing agentic AI workflows for enterprise environments. Focus on how you manage agent autonomy, error handling, and the integration of LLMs with existing enterprise data pipelines.
Managing Large-Scale AI/GenAI Programs
What to coverDiscuss the challenges of leading a 20+ headcount team in delivering AI solutions. Address how you balance technical debt, model performance monitoring, and the specific lifecycle management required for GenAI projects.
Data Science Lifecycle and Governance
What to coverDescribe your methodology for overseeing the end-to-end data science lifecycle, from data ingestion to model deployment. Emphasize how you ensure model accuracy, ethical AI compliance, and scalability in production.
Commercial and Client Solutioning
What to coverHow do you align technical architecture with client business requirements while managing project commercials? Suggestion: Prepare to discuss how you translate complex AI capabilities into value-driven proposals that justify investment.
Project Management Frameworks for AI
What to coverGiven the requirement for project management certifications, explain how you adapt traditional methodologies like Agile or Waterfall to the iterative and often unpredictable nature of AI/ML development.
Behavioural practice
Driving Business Growth
What to coverDescribe a situation where you successfully expanded an existing client account by 30% or more. Focus on the specific actions you took to identify new opportunities and the strategy used to secure the expansion.
Mentoring and Team Development
What to coverProvide an example of how you have mentored a team member to advance their career path. Detail the situation, the specific guidance you provided, and the measurable result of their professional growth.
Managing Client Relationships and NPS
What to coverTell me about a time you turned a challenging client interaction into a positive outcome. Explain how you managed expectations and what steps you took to ensure high customer satisfaction and referenceability.
Leading Through Technical Complexity
What to coverDescribe a project where you had to lead a diverse team of architects and developers through a significant technical roadblock. Explain your role in facilitating the solution and ensuring the project remained on track.
02
Sharpen your knowledge
Topics to prepare
Agentic AI and GenAI Enterprise Architecture
Review the conceptual differences between traditional predictive AI/ML and modern Agentic AI frameworks. Prepare to discuss how to integrate these into enterprise-grade solutions, focusing on scalability, security, and reliability as required for large-scale delivery.
Commercial and Client Relationship Management
Study strategies for managing complex IT project commercials and maintaining high Net Promoter Scores (NPS). Focus on the transition from technical delivery to strategic partnership, ensuring clients become referenceable accounts.
Large-Scale Program Governance
Refine methodologies for managing teams of 20+ headcount. Focus on balancing technical oversight of architects and developers with the administrative requirements of project planning and career path mentoring for direct reports.
Skills to revise
AI/GenAI Program Management
Create a mock project roadmap for an enterprise AI deployment. Include resource allocation for a 20-person team, milestone tracking for GenAI model integration, and risk mitigation strategies for complex data science projects.
Solution Architecture Leadership
Practice articulating technical solution designs to non-technical stakeholders. Focus on translating complex AI architecture into business value to support the target of 30% annual business growth.
Project Management Certification Application
Review core principles from PMP or Prince2 frameworks. Prepare to demonstrate how these formal methodologies are applied specifically to the lifecycle of AI/ML projects, from initial client engagement to final delivery.
04
Your preparation checklist
Prepare a 20+ headcount program case study
Draft a structured overview of a past program where you led a team of 20 or more, specifically highlighting your role in delivering enterprise-grade AI or GenAI solutions, managing technical architects, and meeting project milestones.
Develop a business growth strategy framework
Create a brief proposal or methodology demonstrating how you would identify and capture new business opportunities within existing client accounts to achieve a 30% annual growth target, focusing on commercial management and client relationship expansion.
Document your technical leadership in Agentic AI
Prepare specific examples of how you have overseen the architecture and delivery of Agentic AI and GenAI systems, including how you navigated technical trade-offs and finalized solutions with client stakeholders.
Outline your team mentorship and development approach
Prepare a summary of your leadership philosophy regarding career pathing for technical staff, including how you have successfully mentored architects and developers to improve performance and retention.
Formulate strategic questions for the interview
Prepare questions regarding Capgemini's current AI delivery pipeline, the specific metrics used to track NPS for reference customers, and the organizational structure of the Delivery Excellence community.
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