New opportunity

Gen AI Transformation Leader (MS)

Capgemini Invent · Gurgaon, India

About this role

Capgemini Invent seeks a Gen AI Transformation Leader (MS) in Gurgaon to lead customer transformation programs and define enterprise-grade Azure and generative AI architectures. The role combines transformation delivery, architectural leadership, executive advisory and strategic deal development.

Responsibilities

Define and execute a transformation vision aligned with customer objectives. Establish a Transformation Office, govern initiatives from planning through closure, and manage budgets, resources and financial tracking.
Serve as the main contact between customers and the transformation team. Build relationships with C-level executives, business leaders and partners, and communicate progress and outcomes.
Own Azure and GenAI reference architectures spanning cloud, data, AI and agentic patterns. Lead the design of LLM-based systems, RAG solutions and agentic workflows; act as the final architectural authority for complex engagements. Embed security, privacy, compliance and Responsible AI principles by design.
Lead discovery workshops, pre-sales solutioning and executive presentations. Shape deal strategy, differentiation, value propositions and pricing with sales leadership; own the technical win strategy and contribute to complex proposals and RFP responses.
Work with Microsoft Azure, AI and industry go-to-market teams on joint pursuits and co-selling. Use Microsoft programs, accelerators and funding mechanisms, and represent the firm in Microsoft forums and customer briefings.

Requirements

At least 15 years of experience in enterprise transformation, business consulting and technology strategy, with a strong delivery record, demonstrated P&L contribution and deep expertise in Microsoft-stack transformations.
Bachelor’s degree in Engineering, Computer Science, Technology Management or a related field. A master’s degree is preferred.
Hands-on expertise in Azure Cloud and GenAI architectures, including LLMs, RAG pipelines, agent-based solutions, data platforms and automation. Experience designing end-to-end Microsoft solutions, leading transformations using Azure, DevOps and Power Platform, and shaping complex pre-sales engagements.
Strong leadership, communication, stakeholder influence, problem-solving and executive presentation skills; ability to work amid ambiguity and lead zero-to-one initiatives.

The posting describes the position as permanent.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Generative AIMicrosoft AzureLLMsRetrieval-Augmented GenerationAI agentsAI architectureCloud architectureData platformsAutomationResponsible AISecurityPrivacyComplianceDevOpsMicrosoft Power PlatformEnterprise transformationTechnology strategyBusiness consultingPre-salesSolution architectureExecutive stakeholder managementBudget planningResource allocationFinancial trackingRFP responsesExecutive presentations

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Deliver governed transformation programs
The role defines a customer-aligned transformation vision, establishes a Transformation Office, oversees initiatives through closure, and leads budget, resource and financial tracking.
Own Azure and GenAI architecture
The role is the final architectural authority for complex engagements, defining cloud, data, AI and agentic reference architectures and leading LLM, RAG and agentic-workflow design.
Build safeguards into solution design
Security, privacy, compliance and Responsible AI must be embedded by design, rather than treated as separate concerns after an architecture is chosen.
Advise executives and shape strategic deals
The role is the primary customer contact, communicates outcomes to senior stakeholders, and leads discovery, executive presentations, technical win strategy, proposals and RFP contributions. It also shapes value propositions and pricing with sales leadership.
Develop Microsoft-linked pursuits
The role works with Microsoft Azure, AI and industry go-to-market teams on joint pursuits and co-selling, and uses Microsoft programs, accelerators and funding mechanisms.

Likely challenges to think through

Balance ambitious AI designs with controls
A likely trade-off is moving quickly on LLM, RAG or agentic solutions while meeting the posting’s security, privacy, compliance and Responsible AI expectations. Prepare to explain how architectural decisions and safeguards would be evaluated together; this is a preparation hypothesis, not a reported employer problem.
Make deal promises deliverable
Because the role spans technical win strategy, pricing input and end-to-end program oversight, a likely difficulty is reconciling a compelling proposal with realistic resources, budgets and delivery commitments. Prepare an example of how you would surface assumptions and trade-offs before commitments are made.
Create alignment amid ambiguity
The posting calls for zero-to-one work, executive influence and a customer-aligned transformation vision. A likely challenge is turning differing stakeholder objectives into a workable sequence of initiatives. Prepare to describe how you would establish priorities, governance and clear executive progress reporting.

Practice your answers

Technical practice

How would you turn a customer’s business objectives into a governed transformation plan?

What to coverThe posting calls for a transformation vision, a Transformation Office, and oversight from planning through closure. Suggested preparation: explain how you would set priorities, decision rights, milestones, outcome measures, and executive reporting.

How would you manage resources, budgets, and financial performance across a transformation program?

What to coverThe role includes budget planning, resource allocation, and financial tracking; the posting also seeks demonstrated P&L contribution. Suggested preparation: discuss forecasting, handling variances, and balancing delivery outcomes with commercial constraints.

What would you include in an enterprise-grade Azure and GenAI reference architecture?

What to coverThe posting specifies cloud, data, AI, and agentic patterns and calls for end-to-end Microsoft-based solutions. Suggested preparation: describe the major components, their boundaries, and how the architecture would adapt to customer objectives.

How would you design and evaluate a RAG solution for an enterprise use case?

What to coverThe role explicitly includes LLM-based systems and RAG pipelines. Suggested preparation: cover data preparation, retrieval quality, answer grounding, evaluation, and trade-offs among quality, latency, and cost.

When would you choose an agentic workflow over a simpler LLM-based solution?

What to coverThe posting calls for agent-based solutions and agentic workflows. Suggested preparation: compare the value of multi-step automation with the added complexity of tool access, oversight, failure handling, and evaluation.

How would you embed security, privacy, compliance, and Responsible AI into a GenAI design?

What to coverThe posting requires these principles to be built in by design. Suggested preparation: explain how you would address data access, sensitive information, output risks, monitoring, and decisions that need human review.

How would Azure, DevOps, and Power Platform fit into an end-to-end transformation solution?

What to coverThe posting names all three in connection with large-scale digital transformations. Suggested preparation: describe where each might add value, how you would integrate them, and when you would avoid unnecessary platform complexity.

How would you resolve a disputed architecture decision on a large GenAI engagement?

What to coverThe role is described as the final architectural authority for complex engagements. Suggested preparation: compare options against customer outcomes, operational constraints, and risk, then explain how you would document and communicate the decision.

How would you move from a discovery workshop to a differentiated technical proposal?

What to coverThe posting includes discovery, pre-sales solutioning, RFP responses, value propositions, and pricing work with sales leadership. Suggested preparation: explain how you would test assumptions, shape the solution narrative, and make its value and trade-offs clear without overpromising.

How would you assess a Microsoft joint-pursuit opportunity?

What to coverThe role interfaces with Microsoft Azure, AI, and industry go-to-market teams and may use programs, accelerators, and funding mechanisms. Suggested preparation: discuss how you would check customer fit, technical relevance, commercial value, and any applicable program conditions rather than assume a mechanism is available.

Behavioural practice

Tell me about a time you aligned executives who disagreed on transformation priorities.

What to coverThe posting emphasizes C-level relationships and stakeholder influence. Suggested preparation: use situation, action, and result to show how you surfaced competing objectives, reached a decision, and communicated its consequences.

Describe a zero-to-one initiative you led when the scope was ambiguous.

What to coverThe posting explicitly calls for effectiveness in ambiguity and zero-to-one work. Suggested preparation: use situation, action, and result to explain what you clarified first, how you made decisions with incomplete information, and what changed.

Tell me about a transformation program that went off plan and how you responded.

What to coverThe role covers delivery governance, monitoring, resources, and financial tracking. Suggested preparation: use situation, action, and result to explain how you detected the issue, worked with stakeholders on a recovery plan, and measured the outcome.

Describe a time you had to challenge a proposed technical approach despite commercial pressure.

What to coverThe posting combines final architectural authority with deal shaping and pricing discussions. Suggested preparation: use situation, action, and result to show how you explained the trade-off, protected the customer outcome, and reached a workable decision.

Tell me about a pursuit that required coordination across a customer, sales team, and technology partner.

What to coverThe posting includes strategic pursuits, customer advisory, and Microsoft joint-pursuit work. Suggested preparation: use situation, action, and result to distinguish your contribution to alignment, the proposal, and the eventual outcome.

Sharpen your knowledge

Topics to prepare

Enterprise transformation governance
The posting calls for a customer-aligned transformation vision, a Transformation Office, and oversight from planning through closure. For revision, map the decisions, governance checkpoints and executive communications needed across that lifecycle.
Azure and GenAI reference architecture
The role owns enterprise-grade reference architectures spanning cloud, data, AI and agentic patterns. For revision, compare two architectural approaches for a large transformation and explain the trade-offs that would warrant a final architecture decision.
LLM, RAG and agentic design
The posting explicitly names LLM-based systems, RAG pipelines and agentic workflows. For revision, trace how data reaches a generated answer or agent action, then identify where quality and operational risks arise.
Security and Responsible AI by design
The role must embed security, privacy, compliance and Responsible AI in solutions. For revision, review a hypothetical GenAI architecture and explain which design decisions address each concern; the hypothetical case is a preparation exercise, not a stated project.
Commercial strategy for complex pursuits
The posting includes deal differentiation, value articulation, pricing constructs, technical win strategy and P&L contribution. For revision, explain how a proposed architecture supports a business outcome and what delivery and financial assumptions would need scrutiny.
Microsoft ecosystem pursuits
The role interfaces with Microsoft Azure, AI and industry go-to-market teams on joint pursuits and co-selling, and uses Microsoft programs, accelerators and funding mechanisms. For revision, outline what would need validating with those teams before including any such mechanism in a customer proposal.

Skills to revise

Produce an end-to-end Microsoft solution sketch
Practice drawing an Azure and GenAI solution showing data flow, an LLM or RAG component, agentic interactions where appropriate, and security boundaries. Explain the choices aloud. This prepares for the posting’s hands-on architecture and final-authority responsibilities.
Plan transformation delivery and finances
Practice creating a one-page plan with phases, governance decisions, resource allocation, budget assumptions and financial tracking measures. This reflects the stated responsibility for Transformation Office delivery and program finances.
Run an executive discovery conversation
Practice a short discovery workshop: ask for business objectives and constraints, clarify an ambiguous request, and summarize decisions and open questions for a C-level audience. The posting calls for discovery workshops, stakeholder influence and executive communication.
Draft a technical pursuit narrative
Practice writing a brief RFP-style response that links customer outcomes, Microsoft-based architecture, differentiation, delivery approach and pricing assumptions. This prepares for the stated pre-sales, technical win strategy and proposal responsibilities.
Explain the delivery role of DevOps and Power Platform
Practice walking through how DevOps and Power Platform could fit an end-to-end Azure transformation, including when each adds value and what must be governed. Both are named in the posting; this walkthrough is a preparation suggestion, not a prescribed solution.

Your preparation checklist

Map evidence to the stated requirements
Prepare a one-page record of relevant transformation delivery, Microsoft-stack leadership and P&L contribution, with verifiable outcomes. Note how your qualifications relate to the stated 15+ years and degree requirements; do not fill gaps with assumed experience.
Build a transformation walkthrough
Select an engagement you can discuss and outline the customer objective, transformation vision, governance, executive communication, budget and resource decisions, and results. The posting assigns ownership from planning through closure.
Rehearse an Azure and GenAI design exercise
Sketch an illustrative enterprise reference architecture covering cloud, data, an LLM-based RAG solution and an agentic workflow. Be ready to explain design trade-offs and where Azure, DevOps and Power Platform fit, since the role calls for end-to-end Microsoft solutions.
Show how safeguards shape the design
Add a short review of security, privacy, compliance and Responsible AI decisions to your design exercise. Distinguish controls you have implemented from safeguards you would propose for this hypothetical case.
Prepare a strategic pursuit example
Walk through a discovery-to-proposal or RFP engagement, if available: customer need, solution differentiation, business value, technical win strategy and your contribution to pricing discussions. Practice a concise executive presentation of the choices.
Plan a Microsoft partnership discussion
Prepare an example, if available, of working with Microsoft teams on a joint pursuit or co-sell motion. The posting also mentions programs, accelerators and funding mechanisms; identify what you can substantiate and what you would need to learn.
Write questions for the employer
Ask how this role balances Transformation Office delivery, final architecture decisions and strategic pursuits; how success is measured; and how Capgemini Invent works with Microsoft teams on joint opportunities.

Availability last checked: 5 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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