New opportunity

Marketing AI and Personalization SME

Capgemini · Bangalore, India

About this role

The Marketing AI and Personalization SME will define and drive AI-enabled marketing transformation at Capgemini. This role focuses on identifying, prioritizing, and shaping AI, generative AI, decisioning, and agentic AI use cases to improve marketing effectiveness, customer experience, and operational productivity. This is a business-focused consulting role rather than an AI engineering position. Key Responsibilities: Marketing AI Strategy: Define AI-enabled marketing vision and transformation roadmaps, assess processes for automation, and develop executive business cases. Generative AI for Marketing: Design use cases for content ideation, generation, and localization, including requirements for marketing copilots and human-in-the-loop compliance processes. Agentic Marketing: Identify processes for agent-based orchestration, design human oversight requirements, and collaborate with architects on multi-agent workflows. AI-Driven Personalization: Develop targeting strategies, next-best-action/offer use cases, and decisioning requirements. Responsible AI and Governance: Establish controls for fairness, privacy, and bias mitigation, collaborating with legal and compliance teams. AI Operating Model: Define future-state interaction models between marketers and AI agents, and support change management. Consulting and Pre-Sales: Lead ideation workshops and develop transformation proposals. Required Qualifications: 15+ years of experience in marketing, personalization, customer analytics, or AI consulting. Strong understanding of marketing processes and customer journeys. Practical knowledge of generative AI, predictive AI, and agentic AI concepts. Ability to communicate complex AI concepts to executive stakeholders. Preferred Qualifications: Experience with major marketing ecosystems (Adobe, Salesforce, Pega, Microsoft, Google, AWS, Databricks). Familiarity with LLMs, RAG, prompt design, and recommendation engines. Experience in regulated industries like Financial Services. Proven track record of taking AI use cases from ideation to scaled adoption.

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Skills for this role

Marketing StrategyPersonalizationCustomer AnalyticsMarketing TechnologyAI ConsultingDigital TransformationGenerative AIPredictive AIDecisioningCopilotsAgentic AIResponsible AIPrivacyRisk ManagementHuman-in-the-loopWorkshop FacilitationAdobeSalesforcePegaMicrosoftGoogleAWSDatabricksLarge Language ModelsRetrieval-Augmented GenerationPrompt DesignRecommendation Engines

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

Strategic AI Transformation Roadmap
Define the vision for AI-native marketing by assessing current processes and prioritizing use cases based on business value, feasibility, and data readiness. Success requires translating complex AI capabilities into actionable executive business cases and investment plans.
Responsible AI and Governance Frameworks
Establish robust controls for fairness, privacy, and bias mitigation. You must collaborate with legal and compliance teams to define human-in-the-loop requirements and monitoring protocols to manage risks like hallucinations and regulatory non-compliance.
Operating Model and Change Management
Design the future-state interaction model between human marketers and AI agents. This involves identifying new roles, defining ways of working, and creating playbooks to ensure successful organizational adoption and workforce enablement.
Consulting and Pre-Sales Leadership
Lead ideation workshops and shape transformation proposals for clients. You must effectively communicate the value of generative and agentic AI to non-technical stakeholders while demonstrating how these solutions integrate with existing marketing ecosystems.

Likely challenges to think through

Bridging Technical AI and Marketing Strategy
The role requires deep business acumen to avoid the trap of focusing on technology for its own sake. Prepare by practicing how to articulate the 'why' behind AI adoption in marketing terms, focusing on operational productivity and customer experience rather than just model performance.
Navigating Regulatory and Ethical Constraints
Implementing AI in marketing, especially in regulated sectors like Financial Services, creates tension between innovation and risk. Prepare by developing a structured approach to 'Responsible AI' that balances the speed of generative content with the necessity of strict compliance and auditability.
Managing Multi-Agent Workflow Complexity
Designing agentic marketing workflows involves orchestrating complex, autonomous systems that require human oversight. Prepare by researching frameworks for human-in-the-loop design and escalation paths to ensure that automated decisions remain aligned with brand standards and business rules.

Practice your answers

Technical practice

Prioritizing AI Marketing Use Cases

What to coverExplain your framework for evaluating AI use cases based on business value, feasibility, and data readiness. Discuss how you balance quick wins with long-term transformation goals while ensuring alignment with marketing objectives.

Designing Human-in-the-Loop Processes

What to coverDescribe how you would design oversight mechanisms for generative AI content production. Focus on balancing the efficiency of automation with the necessity of compliance, brand safety, and quality assurance.

Agentic Marketing Orchestration

What to coverHow do you identify which marketing processes are suitable for agent-based automation versus human-led tasks? Discuss the architectural considerations for multi-agent workflows and the importance of defining clear boundaries for autonomous actions.

AI-Driven Personalization and Decisioning

What to coverDetail your approach to integrating predictive insights with business rules for next-best-action strategies. Address how you handle eligibility, suppression, and arbitration in complex, multi-channel customer journeys.

Responsible AI and Governance Frameworks

What to coverWhat specific controls would you implement to mitigate risks like bias, hallucination, and privacy violations in marketing AI? Explain how you would collaborate with legal and compliance teams to operationalize these requirements.

Marketing AI Operating Models

What to coverHow do you define the future-state interaction model between human marketers and AI agents? Discuss the impact on team roles, necessary skill shifts, and the change management strategies required for successful adoption.

RAG and LLM Application in Marketing

What to coverExplain how Retrieval-Augmented Generation (RAG) can be applied to improve the accuracy and relevance of marketing copilots. Discuss the importance of grounding AI responses in proprietary brand data and customer context.

Scaling AI from Ideation to Adoption

What to coverDescribe your methodology for taking a proof of concept to a scaled enterprise solution. Highlight the common pitfalls in scaling AI initiatives and how you address them through robust documentation and reusable playbooks.

Behavioural practice

Translating Complex AI for Executives

What to coverDescribe a situation where you had to explain a complex AI concept to a non-technical stakeholder to secure buy-in. Focus on how you simplified the narrative to emphasize business outcomes and ROI without losing technical accuracy.

Managing Stakeholder Conflict in Transformation

What to coverProvide an example of a time you faced resistance to a new AI-enabled process. Explain how you identified the root cause of the resistance and the specific steps you took to facilitate alignment and drive adoption.

Facilitating Ideation Workshops

What to coverTell me about a time you led a workshop to identify new opportunities for digital transformation. How did you structure the session to ensure diverse stakeholder input and prioritize actionable outcomes?

Navigating Regulatory Constraints

What to coverShare an experience where you had to implement a solution within a highly regulated environment (e.g., Financial Services). How did you balance the need for innovation with strict privacy and compliance requirements?

Sharpen your knowledge

Topics to prepare

AI-Enabled Marketing Operating Models
Review how to restructure marketing teams to integrate AI agents and copilots. Exercise: Draft a future-state interaction model for a campaign team, defining where human-in-the-loop oversight is required for content approval and decisioning. This is relevant to the role's focus on organizational change management and defining new ways of working.
Responsible AI and Governance in Marketing
Study frameworks for mitigating bias, hallucination, and privacy risks in customer-facing AI applications. Exercise: Create a checklist for auditing an AI-driven personalization engine to ensure compliance with data privacy and fairness standards. This is essential for the role's responsibility in establishing controls for regulated industries.
Agentic Marketing Workflows
Conceptualize how autonomous agents can orchestrate multi-step marketing processes like journey monitoring and performance optimization. Exercise: Map out a multi-agent workflow for a customer retention campaign, identifying specific hand-off points between AI agents and human marketers. This directly addresses the requirement to design agent-based orchestration.

Skills to revise

Executive Business Case Development
Practice translating technical AI capabilities into financial and operational value propositions. Exercise: Develop a one-page business case template for a generative AI content ideation tool, focusing on ROI, cycle time reduction, and risk mitigation. This is critical for the consulting and pre-sales aspects of the role.
Workshop Facilitation for AI Ideation
Refine techniques for leading cross-functional teams through AI use-case prioritization. Exercise: Design a 90-minute workshop agenda to help stakeholders identify and rank AI marketing use cases based on feasibility and business impact. This is a core requirement for leading ideation sessions with clients.
Marketing Ecosystem Integration Strategy
Understand how to bridge AI capabilities with platforms like Salesforce, Adobe, or Pega. Exercise: Create a high-level architecture diagram showing how a RAG-based marketing copilot would integrate with existing CRM data and campaign management tools. This is relevant to the preferred experience with major marketing ecosystems.

Your preparation checklist

Develop a Marketing AI Transformation Framework
Prepare a structured approach for assessing marketing maturity and identifying AI use cases. Create a one-page visual framework that demonstrates how you prioritize AI initiatives based on business value, technical feasibility, and data readiness, specifically addressing generative and agentic AI.
Prepare a Case Study on AI-Driven Personalization
Draft a concise project walkthrough detailing a past initiative where you implemented predictive or decisioning models. Focus on the business outcome, the integration of customer signals, and how you managed the transition from traditional segmentation to next-best-action strategies.
Draft a Responsible AI Governance Checklist
Create a checklist for mitigating risks in marketing AI, such as hallucination, bias, and privacy concerns. Include specific protocols for human-in-the-loop oversight and compliance requirements suitable for a regulated industry like Financial Services.
Design a Marketing Operating Model Proposal
Develop a conceptual model illustrating the future-state interaction between human marketers and AI agents. Outline the necessary changes to roles, workflows, and governance forums required to support scaled AI adoption within a large enterprise marketing organization.
Formulate Strategic Questions for the Interview
Prepare thoughtful questions regarding Capgemini's current marketing AI maturity, the primary challenges clients face in scaling agentic workflows, and how the firm balances rapid innovation with the strict governance requirements of their regulated clients.

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