AI Innovation Engineer, Deutsche Borse Delivery Team, Cloud in London

Minimum qualifications:

• Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
• 6 years of experience in software or data engineering.
• Experience solving real-world problems using machine learning methodologies (deep learning, reinforced learning), model identification, selection and AI operations (e.g., model monitoring).
• Experience solving real-world problems using Generative AI and agentic orchestration utilizing frameworks (e.g., LangChain, CrewAI, or Vertex AI Agent Builder) and vector databases.
• Experience with one of the following programming languages: Python, Go, or Java.
• Experience with design patterns, testing frameworks, and API contract design.

Preferred qualifications:

• Experience in financial services, and with the regulatory and operational clearing, settlement, or custody.
• Experience with FSI regulatory practices and data residency, encryption at rest/transit (CMEK), and "explainable AI" requirements in banking.
• Experience with data modeling of relational, NoSQL, and analytical data modeling (Star Schema, Data Vault, etc.).
• Experience working in a high-maturity DevOps culture (trunk-based development, automated testing, blue/green deployments).
• Experience in BigQuery, Vertex AI, Dataflow, and Pub/Sub with an ability to drive the discovery phase, moving from a vague business problem to a structured PRD and a working technical demo.

About the job:

The Global Solutions and Consumer AI team accelerates customer value and increases adoption by delivering innovative, repeatable, and enterprise-ready solutions focused on business value. In this role, you will collaborate with clients to transform initial concepts into reality. You will create solutions using the latest machine learning and Generative AI technologies to replace traditional workflows for a customer in the capital markets finance industry. You will work at the heart of Financial Market Infrastructures (FMIs) including high-stakes clearing, settlement, and custody environments to identify where AI can drive systemic efficiency. You will act as a motivated innovator and builder who can operate with minimal guidance. You will not only code and create functional prototypes but also help define the Critical User Journeys (CUJs) and technical requirements that turn a Proof-of-Concept (POC) into a scalable, production-ready solution usable across a broad base of the company Cloud Platform (GCP) clients.

Responsibilities:

• Design and build autonomous agentic workflows utilizing machine learning and Generative AI technologies as part of a fully autonomous or human-in-the-loop agentic workflow.
• Partner with client leads (business user) to identify high-impact AI use cases. Translate these into Product Requirement Documents (PRDs), clearly defining CUJs and success metrics.
• Evaluate and integrate AI solutions with modern data foundations, including relational databases, data lake houses, and real-time streaming architectures.
• Ensure all prototypes are built with a "production-first" mindset. Implement basic CI/CD pipelines and utilize Infrastructure-as-Code (IaC) (e.g., Terraform) to ensure environments are reproducible and secure.
• Create clear technical guides to ensure a seamless hand-off from POC to engineering teams.

The company is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.