Data Product Manager – AI Platform

About

The Data Product Manager – AI Platform position is attached to the Head of Data Platform Products, within the Data Office and Services (DOS) team of Hermès Data Technology and Innovation (HDTI).

Based in Pantin.

As a member of the Data Platform Product Management team, you will be responsible for a portfolio of products, platforms, and services that make up the Group's AI infrastructure. This scope includes, but is not limited to, agentic AI tools (such as Claude Code), the LLM Gateway, and an LLM model catalog. Adopting a product-oriented approach, this role includes structuring and deploying common technical foundations and tooling, as well as managing the lifecycle of AI infrastructure products, from their commissioning to major evolutions, obsolescence, or decommissioning.

Main Activities:

Product Management & Platform Product Vision

• Define and carry the AI platform product vision in line with the DOS strategy
• Structure the offering into platform products and services
• Build and prioritize product backlogs based on business value, transversal impact, and pooling
• Write product sheets, user stories, functional specifications, and acceptance criteria (DoR/DoD)
• Lead product rituals: roadmap review, backlog refinement, arbitration sessions

Industrialization & Service Catalog

• Build and maintain the AI services catalog (products, APIs, common tools)
• Define and manage product SLOs/SLAs (availability, performance, time to value)
• Formalize operational and support runbooks in collaboration with Run teams
• Implement incident management processes (N1/N2/N3 classification, escalations, post-mortems)
• Integrate a FinOps approach: cost modeling, showback/chargeback, and usage optimization

Internal Adoption and Go-to-Market

• Manage the adoption of AI Platform products by internal teams (technical, data, application)
• Define the adoption strategy: target segmentation, value proposition, communication channels
• Orchestrate progressive rollouts: pilots, early adopters, generalization
• Produce user documentation: guides, tutorials, FAQs, best practices
• Lead onboarding and training sessions
• Implement feedback loops (interviews, NPS, usage analytics) for continuous improvement

Product Analytics & KPIs

• Define key AI platform KPIs: adoption, usage, performance, costs, and reliability
• Implement product observability tools
• Co-build executive steering dashboards
• Analyze usage to identify: optimization opportunities, evolution needs, rationalizations
• Measure the business value and ROI of AI services

Governance and Compliance

• Participate in architecture and AI governance committees in support of the Head of Data Platform Products
• Contribute to the definition and formalization of non-functional requirements, particularly regarding security, performance, scalability, resilience, and compliance
• Work closely with the Design Authority / Enterprise Architecture to ensure overall AI architecture coherence

Vendor Management

• Manage relationships with AI vendors (roadmap, support, pricing, compliance)
• Evaluate and select vendors based on use cases
• Maintain a product-oriented watch on the AI ecosystem (models, platforms, uses, and regulations)
• Share market insights with the DOS team

Communication & Stakeholder Management

• Present the product roadmap to stakeholders
• Document product decisions and governance rules
• Lead user forums and AI communities of practice

Profile

Education & Experience

• Master's degree (Bac+5) in Engineering, Computer Science, Data, AI, or equivalent
• Minimum 5 years of experience in Product Management, including at least 2 years on AI/ML products
• Proven experience in generative AI and LLMs (production deployment desired)
• Experience in AI agent architecture and orchestration (a plus)

Skills

• Generative AI & LLMs: Understanding of LLM architectures (prompting, RAG), platforms (Claude, OpenAI, Gemini), agent orchestration
• Product Management: End-to-end management (discovery, delivery, adoption), roadmaps, product analytics, and KPIs
• Cloud & Infrastructure: AWS or Azure (architecture, costs, basic security), Python/TypeScript code reading (intermediate level)
• Governance & Compliance: Knowledge of GDPR, awareness of the European AI Act and AI ethics

Soft Skills

• Clear technical communication adapted to different audiences (executive, technical, business)
• Transversal leadership and ability to unite without hierarchical authority
• Stakeholder management: managing multiple interlocutors (IT, Cyber, Legal, business units)
• Autonomy, rigor, and a sense of internal customer service
• Ability to prioritize and arbitrate with pedagogical skill
• Professional English proficiency, both spoken and written, in technical and product-oriented environments.