Head of IT AI Platform

MISSION CONTEXT

Within the Group IT organization at ODDO BHF, the Head of IT AI Platform leads the design, deployment, and scaling of the Group’s enterprise AI Platform.

This role focuses on operating AI capabilities (GenAI, LLMs, agents) as a shared enterprise platform , enabling business domains to develop and run AI use cases at scale within a secure and governed framework.

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MAIN MISSION

Define, deliver, and operate a scalable, secure, and industrialized AI Platform , and enable its adoption across the Group by:

• Treating AI capabilities as products
• Enabling AI lifecycle industrialization (LLMOps / MLOps)
• Driving self-service AI adoption
• Ensuring governance, risk control, and scalability

KEY RESPONSIBILITIES

1. AI Platform Strategy and Operating Model

• Define and own AI Platform IT vision, roadmap, and operating model
• Align with business priorities and Data & AI strategy
• Define platform KPIs (usage, performance, cost, adoption)

Manage platform budget and Investments

. AI Platform Ownership (Run & Change)

• Own the AI agentic platform (Prisme AI) as a product:
• reliability, performance, scalability
• cost control (LLM usage / API consumption)
• Deploy and maintain AI solutions such as Claude, Azure Foundry, MS Copilot
• Ensure monitoring, lifecycle management, and continuous improvement

AI Platform Architecture & Integration

• Lead implementation and scaling of Prisme AI platform, Claude, Azure Foundry, MS Copilot
• Define architecture:
• integration with Snowflake (data layer)
• integration with LLMs and applications

Develop connectors and integration patterns

AI Lifecycle Industrialization (LLMOps / MLOps)

• Define and operate:
• model lifecycle (deploy, monitor, retrain)
• versioning and CI/CD for models
• Monitor performance, usage, cost, reliability
• Enable production deployment at scale

AI Governance, Risk & Compliance

• Align to the Data & Digital services governance, implement governance framework:
• access policies
• model selection
• risk management (bias, hallucination, explainability)
• Ensure compliance with data confidentiality and regulatory constraints
• Secure AI usage across the enterprise

AI Enablement & Self-Service

• Enable business adoption via AI marketplace / catalog and reusable components (agents, prompts, APIs)
• Improve developer and user experience
• Promote AI adoption across business units

Delivery & Value Creation

• Ensure end-to-end delivery of AI platform capabilities
• Align priorities with Data & Digital Services
• Ensure value generation and adoption

Leadership & Organization

• Lead AI / platform / ML engineering teams
• Structure scalable AI engineering capabilities
• Manage internal teams and external partners

Business Partnership with Data & Digital Services

• Co-lead AI transformation with Data & Digital Services
• Align IT roadmap, priorities, and investments
• Enable industrialization of AI use cases
• Ensure coordination across IT

PROFILE & SKILLS

1. Profile

A senior AI and platform leader combining:

• AI platform mindset (AI as a scalable product)
• Strong technical understanding of AI ecosystems
• Industrialization experience (POC to production)
• Risk-aware leadership (AI governance & compliance)
• Business-oriented mindset
• Strong execution capability

2. Core Competencies

A. AI Platform Leadership

• Experience designing enterprise AI / GenAI platforms
• Strong understanding of:
• LLM ecosystems
• APIs, model serving
• AI integration in enterprise systems

B. AI Lifecycle & MLOps

• Experience with:
• MLOps / LLMOps practices
• model deployment, monitoring, retraining
• Experience industrializing AI at scale

C. AI Enablement

• Experience building AI marketplaces and reusable AI components
• Strong focus on self-service adoption

D. AI Governance & Risk

• Knowledge of:
• AI risks (bias, explainability, hallucination)
• regulatory constraints
• Ability to define governance frameworks

E. xuezdbg Integration with Data Platform

• Good understanding of:
• data pipelines feeding AI
• interaction with Snowflake and data products

F. Leadership & Stakeholder Management

• Leadership of IT teams in a product driven organisation
• Strong interaction with Data & Digital Services and business
• Ability to balance innovation, cost, and risk

3. Technical Skills

• LLM platforms and APIs
• AI orchestration, agents, prompt frameworks
• MLOps / LLMOps tooling
• Data pipelines integration
• Security & IAM for AI usage
• Azure services

4. Experience

• 10+ years in Data / AI / Platform engineering
• Leadership experience in AI programs
• Proven experience:
• GenAI / AI platform implementation
• AI industrialization at scale
• Experience in regulated environments preferred