Full Stack AI Engineer (f/m/x) - Innovation and the TDI Chief Strategy Office
Deutsche Bank
- Location
- Berlin Otto-Suhr-Allee 16
- Work model
- On-Site
- Level
- Mid
- Posted
- Sep 4, 2026
Skills
About this role
Job Description
About the job: Innovation and the TDI Chief Strategy Office 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. DB Technology is a global team of tech specialists, spread across multiple trading hubs and tech centres. We have a strong focus on promoting technical excellence – our engineers work at the forefront of financial services innovation using cutting-edge technologies. Our Berlin location is our most recent addition to our global network of tech centres and growing strongly. We are committed to building a diverse workforce and to creating excellent opportunities for talented engineers and technologists. Our tech teams and business units use agile ways of working to create #GlobalHausbank solutions from our home market. The team's focus is turning Artificial Intelligence, Large Language Models (LLMs) and Agentic AI into products people across the bank use every day — moving fast from prototype to production, and creating measurable value for clients and the bank. As a Full Stack AI Engineer (f/m/x) in the Innovation team of the TDI Chief Strategy Office you will build AI-powered products end to end, with a particular focus on the user-facing layer. You will design and implement the interfaces through which colleagues and clients across the bank experience AI, as well as the services and agents that sit behind them. This role suits an engineer who takes user experience seriously and wants to see ideas move from prototype to something people genuinely rely on. Your key responsibilities You design and build the front end of our AI products — responsive, accessible web applications that make complex agentic and LLM-driven capabilities feel simple to use. You own the interface from component design through to production. You implement the interaction patterns that AI products depend on: streaming responses, conversational and multi-turn interfaces, human-in-the-loop review steps, citation and source display, agent-driven user interfaces (A2UI), and clear handling of latency, partial results and failure states. You develop the backend services and APIs that power those interfaces, and integrate LLM and agent capabilities. You work closely with design and product to translate rough concepts into interfaces you can put in front of real users quickly, and you iterate on what you learn from them. You contribute to engineering standards across the stack, including component libraries and design system usage, testing, code quality, CI/CD and observability, and take full ownership of the components you deliver. You work in a cross-functional team across engineering, product, design and infrastructure to take high-impact AI use-cases from problem framing to deployment. You communicate technical concepts and results effectively to both technical and non-technical audiences, and demonstrate progress through working software. Your skills and experience University degree in a technical or quantitative field (e.g., computer science, software engineering, mathematics, physics, etc.). Several years of professional experience building and shipping software products, including at least two years where front-end development was your main focus. Strong knowledge of modern front-end engineering: React (or a comparable framework), state management, component architecture, and CSS/styling approaches such as Tailwind. Experience building interfaces on top of APIs, including streaming and real-time data (e.g., SSE or WebSockets), and a good understanding of how front-end and backend design decisions affect one another. Experience developing backend services and REST APIs, ideally in Python with a framework such as FastAPI — but strong engineers from other backend stacks who are ready to adapt