Head of AI Platforms

THE ORGANISATION
A leading financial services organisation headquartered in Munich, operating across insurance, asset management, and financial infrastructure at scale. With a strong balance sheet, a growing appetite for technology-led transformation, and thousands of users across Europe, the business is investing heavily in AI to unlock operational efficiency, accelerate decision-making, and build a long-term data competitive advantage.

This is a newly created Director-level role sitting at the heart of that agenda: responsible for defining and delivering the AI platform strategy that will underpin the organisation's AI capabilities for the next decade.

THE ROLE
The Head of AI Platforms will own the end-to-end design, delivery, and governance of the organisation's AI platform engineering function. Reporting directly to the Chief Technology Officer (or Chief Data Officer), this leader will build and lead a team of AI Platform and MLOps Engineers, and partner closely with Data Science, Architecture, Compliance, and Business stakeholders to ensure AI can be deployed at scale, securely, and in a regulated context.

This is a hands-on leadership role: you will set direction but also be expected to be deeply technical, credible with engineers, and comfortable operating in a complex regulated environment.

KEY RESPONSIBILITIES
Define and own the AI platform strategy: including infrastructure, tooling, deployment frameworks, and standards for how AI is built and shipped across the organisation.
Build, lead, and develop a high-performing team of AI Platform Engineers and MLOps specialists, hiring for both near-term delivery and long-term capability.
Design and implement scalable MLOps pipelines: covering model training, versioning, deployment, monitoring, and retraining: in a regulated financial services context.
Establish the organisation's AI governance and compliance framework: model risk management, explainability standards, audit trails, and alignment with BaFin / Solvency II requirements.
Partner with Data Science and Analytics teams to accelerate the path from model experimentation to production deployment, reducing time-to-value for AI initiatives.
Own the AI infrastructure stack: cloud-based platform architecture (Azure / AWS), feature stores, vector databases, LLM orchestration frameworks, and GPU compute provisioning.

CANDIDATE PROFILE
Essential:
Significant experience in data and AI engineering, with a minimum of 5 years in senior or leadership roles within a regulated financial services environment (insurance, banking, or asset management strongly preferred).
Proven track record of building and leading AI or data platform teams: hiring, developing, and retaining senior engineering talent.
Deep technical expertise in MLOps and AI infrastructure: model deployment pipelines, containerisation (Docker/Kubernetes), feature engineering at scale, and model monitoring in production.
Hands-on experience with cloud-native AI platforms: Microsoft Azure (Azure ML, Azure AI Studio, Microsoft Fabric) and/or AWS (SageMaker) at enterprise scale.
Fluent in German and English (both written and spoken); essential for stakeholder engagement across the organisation.

Advantageous:
Experience with LLM deployment, RAG architectures, and agentic AI systems in a production environment.
Familiarity with Microsoft Fabric, OneLake, and the broader Microsoft data and AI ecosystem.
Background in insurance-specific data domains: claims, underwriting, actuarial modelling, or fraud analytics.
Experience operating in a matrix organisation and influencing without direct authority across technology and business functions.

WHAT'S ON OFFER
A Director-level mandate with real organisational authority and budget to build something significant.
Direct reporting line to C-suite with genuine executive visibility and influence over the AI strategy.
Competitive base salary, performance bonus, and long-term incentive package commensurate with Director level in Financial Services.
A hybrid working model with a Munich base: typically 3 days on-site.
The opportunity to define how AI is built and deployed at a major European financial institution: at a pivotal moment in the technology's maturity.