D
Deutsche Bank
AI Adoption Manager
Skills
Google Cloud PlatformData EngineeringPythonData ScienceTensorFlowMachine LearningAIWorkday
2 months ago
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Important information
Contract type:
Permanent
Location:
Ireland
Work mode:
Onsite
Published on:
14 August 2026
What they need
- Deutsche Bank’s Innovation team identifies, evaluates, and incubates cutting-edge technical innovation
- It is part of the Chief Strategy Office of the bank’s Technology, Data & Innovation (TDI) function and works globally with all business lines and infrastructure functions of the bank. A focus of the team is to create value for clients and the bank using Artificial Intelligence, Large Language Models (LLM), Agentic AI and other advanced data-driven technologies
- You will work with AI Developers and Users across Deutsche Bank to design and deliver scalable, resilient AI solutions from concept to production
- This role sits at the intersection of engineering excellence and rapid experimentation, helping turn high-impact ideas into robust capabilities that can be adopted at scale
- Working with AI developers and users across Deutsche Bank to accelerate design, and deliver high-quality software products that use AI and other advanced data-driven technologies to create sustainable value for the Bank. Helping ensure solutions are scalable, secure and production-ready
- Providing hands-on technical support, establishing engineering standards. Staying close to critical system components and assist in the resolution of complex technical challenges
- Working with our AI colleagues across Deutsche Bank to ensure the successful technical delivery of innovation initiatives through to production
- Working in a cross-functional team across engineering, product, design and infrastructure teams to identify, evaluate and execute high impact AI use-cases
- Helping shape and evolve AI architecture and best practices with our innovation team and bank-wide developer community, contributing reusable frameworks, integration patterns, and deployment standards that accelerate future innovations
- Communicating technical concepts and results effectively to both technical and non-technical audiences, and measure success by the business value the solutions generate across our AI Platform- Experience in applying AI, machine learning and/or data science in business and/or academia
- University degree in a technical or quantitative field (e.g., computer science, mathematics, physics, economics, etc.), preferably a Master’s or Doctoral degree or work equivalent
- Knowledge of ML Ops spanning ML, data engineering, cloud platforms, CI/CD, model deployment, monitoring, and AI governance to reliably operate ML solutions at scale
- Strong knowledge of Python and ideally one other programming language, as well as relevant data science or engineering frameworks (e.g., scikit-learn, TensorFlow, Spark, LangChain etc.). Knowledge of GCP or another major cloud platform. Experience building solutions that leverage LLMs. Familiarity with agentic AI frameworks and orchestration patterns (E.g. Google ADK, LangGraph, MCP) is considered an advantage
- 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
- Experience designing and delivering production-grade AI and software products in enterprise environments- End Date: August 16, 2026
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