AI Innovation Engineer, Deutsche Borse Delivery Team, Cloud
Role details
Job location
Tech stack
Job description
- 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.
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Requirements
Do you have experience in Test automation?, Do you have a Bachelor's degree?, * 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., * 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.