Team / division overview

The role sits at the intersection of hands-on delivery and strategic influence. You will work directly with engineers, analysts, delivery leads, and business stakeholders to identify meaningful AI use cases, build practical examples, coach teams, and remove blockers to adoption. At the same time, you will translate what is being learned on the ground into clear recommendations for leadership, tooling, governance, roadmap choices, and ways of working.

Reporting into the Head of Corporate Functions (CF) Technology, you will be embedded in the area where AI adoption needs to happen. You will also work closely with the DWS AI Centre of Excellence, ensuring that Corporate Functions is both aligned to enterprise AI direction and actively shaping it through real delivery experience. You will help create and nurture the Corporate Functions AI Community of Practice, so that knowledge, experimentation, and adoption are shared across teams rather than remaining isolated in individual pockets.

Your responsibilities

- Act as the primary AI champion embedded within the delivery and operational teams, working alongside engineers, analysts, and delivery leads to embed AI into everyday practice.
- Lead and facilitate the AI Open House and equivalent adoption programmes including curating peer wins, facilitating skill-building segments, and visibly resolving blockers.
- Coach individuals and teams on practical AI use, from prompt engineering and gen-AI features through to building RAG pipelines and agentic workflows.
- Serve as the primary convenor and energiser of the AI Community of Practice ensuring it has rhythm, relevance, and genuine peer ownership.
- Curate and grow a shared knowledge base of AI use cases, prompt libraries, lessons learned,



and emerging tools relevant to the team.
- Design and run lightweight experimentation programmes including challenges, hackathons, discovery sprints that surface new AI applications and build confidence across teams.
- Act as the CF technology team's primary AI thought leader and strategic advisor to leadership translating field-level insight into strategic recommendations.
- Stay current with AI developments across the industry particularly in financial services and bring relevant intelligence into AI CoE leadership conversations and roadmap decisions.
- Advise CF business stakeholders on how AI can be applied to their specific domains, translating technical capability into business value language.
- Build, test, and iterate on AI-powered tools, prototypes, and integrations demonstrating feasibility and sparking wider adoption through working examples.
- Design and implement end-to-end AI solutions including RAG pipelines, LLM-powered applications, and agentic workflows that connect AI to real business processes.
- Evaluate internal and SaaS AI models, platforms, and tooling including LLMs, agentic frameworks, and productivity tools and make grounded recommendations based on practical, production-aware experience.

We are looking for Demonstrable hands-on experience building software,



with confidence working in a modern development environment and credibility with engineering teams. Practical, working experience with AI models and tools including LLMs, prompt engineering, AI-assisted coding tools such as GitHub CoPilot or equivalent.

Demonstrable delivery of at least one RAG implementation, an agentic workflow, a fine-tuned model, or a production LLM integration. A genuine track record of driving AI adoption within an organization, making it happen at the team level and measuring what changed. Experience working in or closely with technology teams in complex organizations — ideally within financial services, professional services, or similarly regulated environments.

Demonstrated ability to work across multiple organizational layers from coaching junior developers to briefing senior leadership. Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs.

Proficiency in Python (strongly preferred) and comfort working in a modern development environment. Working knowledge of LLM APIs such as OpenAI, Anthropic, Azure OpenAI, or equivalent and experience building applications on top of them beyond simple prompting. Hands-on experience with AI development tooling: vector databases, embedding models, orchestration frameworks, and evaluation and observability approaches.

Understanding of agentic AI patterns, including tool use, planning, multi-agent coordination with experience designing or building systems that use them. Understanding of how regulated financial services organizations operate including data sensitivity, compliance constraints, and the specifi

📌 Corporate Functions Ai Strategy And Adoption Lead, Director (España)
🏢 Deutsche Bank
📍 España