Marketing AI and Personalization SME

Capgemini; Bengaluru; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Capgemini in Bengaluru seeks a Marketing AI and Personalization SME to drive AI-enabled marketing transformation, focusing on business use cases, solution shaping, and value realization.

The role combines strong marketing knowledge with practical AI capabilities, emphasizing responsible AI, governance, and measurable outcomes for client engagements.

Qualifications

• Over 10 years of experience across marketing, personalization, analytics, and AI-driven transformation.
• Strong marketing process knowledge with practical AI concept understanding.
• Ability to communicate AI concepts to executives and non-technical stakeholders.
• Experience in enterprise marketing ecosystems and technology platforms.

Responsibilities

• Define the AI-enabled or AI-native marketing vision and transformation roadmap.
• Assess current marketing processes to identify opportunities for AI augmentation or automation.
• Prioritize AI use cases based on value, feasibility, risk, data readiness, and adoption requirements.
• Define the role of AI across planning, content, audiences, journeys, decisioning, and measurement.
• Develop executive business cases and investment recommendations.
• Lead ideation and prioritization workshops with clients and stakeholders.

Skills

Marketing strategy

Personalization

Customer analytics

Marketing technology

AI consulting

Digital transformation

AI governance

Tools

Adobe

Salesforce

Pega

Microsoft

Google

AWS

Databricks

Job description

Job Description

The Marketing AI and Personalization SME will define and drive AI-enabled marketing transformation. The role will identify, prioritize, and shape AI, generative AI, decisioning, and agentic AI use cases that improve marketing effectiveness, customer experience, and operational productivity.

The candidate should combine strong marketing knowledge with practical knowledge of AI capabilities. This is not an AI engineering role. The primary focus is on business use cases, solution shaping, operating models, adoption, responsible AI, and value realization.

Key Responsibilities

Marketing AI Strategy

• Define the AI-enabled or AI-native marketing vision and transformation roadmap.
• Assess current marketing processes to identify opportunities for AI augmentation or automation.
• Prioritize AI use cases based on business value, feasibility, risk, data readiness, and adoption requirements.
• Define the role of AI across marketing planning, content, audiences, journeys, decisioning, operations, and measurement.
• Develop executive business cases and investment recommendations.

Generative AI for Marketing

• Define use cases for content ideation, generation, variation, summarization, review, and localization.
• Develop requirements for marketing copilots and knowledge assistants.
• Design human-in-the-loop processes for content generation, approval, and compliance review.
• Identify opportunities to reduce campaign development and content production cycle times.
• Define integration requirements between generative AI capabilities and content, campaign, and workflow platforms.

Agentic Marketing

• Identify marketing processes suitable for agent-based orchestration or automation.
• Define use cases for campaign planning, audience analysis, journey monitoring, content operations, marketing analytics, and performance optimization agents.
• Design human oversight, escalation, audit, and approval requirements.
• Collaborate with AI architects to define multi-agent workflows and platform requirements.
• Establish boundaries for autonomous and human-approved actions.

AI-Driven Personalization and Decisioning

• Define AI-enabled segmentation and propensity-based targeting strategies.
• Develop next-best-action, next-best-offer, and recommendation use cases.
• Define decisioning requirements, including eligibility, prioritization, suppression, arbitration, and contact policies.
• Help connect customer signals, predictive insights, contextual information, and business rules.
• Partner with analytics teams to define model use cases and measurement approaches.

Responsible AI and Governance

• Define responsible AI controls for marketing use cases.
• Establish transparency, explainability, fairness, privacy, human oversight, and audit requirements.
• Identify risks related to hallucination, bias, intellectual property, inappropriate content, customer discrimination, and regulatory compliance.
• Collaborate with legal, privacy, compliance, model risk, security, and brand teams.
• Define monitoring requirements for AI-generated content and AI-driven customer decisions.

AI Operating Model and Adoption

• Define how marketing roles and processes will change through AI adoption.
• Develop the future-state interaction model between marketers, agencies, platforms, copilots, and AI agents.
• Identify new roles, skills, governance forums, and ways of working.
• Support change management, training, adoption, and workforce enablement.
• Create reusable Marketing AI playbooks and maturity models.

Consulting and Pre-Sales

• Lead Marketing AI ideation and prioritization workshops.
• Develop AI transformation proposals, proofs of concept, and executive presentations.
• Shape Marketing AI opportunities with business, technology, data, and AI stakeholders.
• Create Marketing AI points of view, demonstrations, accelerators, and reusable solutions.

Primary Skills

• 10+ years of experience across marketing, personalization, customer analytics, marketing technology, AI consulting, or digital transformation.
• Strong understanding of marketing processes, customer journeys, segmentation, campaign management, and personalization.
• Practical knowledge of generative AI, predictive AI, decisioning, copilots, and agentic AI concepts.
• Experience identifying and prioritizing AI use cases.
• Understanding of responsible AI, privacy, risk, and human-in-the-loop controls.
• Ability to communicate AI concepts to marketing and executive stakeholders without unnecessary technical complexity.
• Strong business-case development, workshop facilitation, and executive storytelling capabilities.

Preferred Experience

• Experience with Adobe, Salesforce, Pega, Microsoft, Google, AWS, Databricks, or similar AI and marketing ecosystems.
• Familiarity with large language models, retrieval-augmented generation, prompt design, AI agents, recommendation engines, and predictive models.
• Experience in Financial Services or another regulated industry.
• Experience taking AI use cases from ideation through proof of concept, pilot, and scaled adoption.
• Knowledge of content supply chains, digital asset management, campaign workflows, and marketing operations.