Minimum qualifications:

• Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
• 7 years of experience in software or data engineering, including one or more programming languages (e.g., Python, Go, Java), and with design patterns, testing frameworks, and API contract design.
• Experience using machine learning methodologies (deep learning, reinforced learning), model identification, selection and AI operations (e.g., model monitoring).
• Experience using Generative AI and agentic orchestration utilizing frameworks (e.g., LangChain, CrewAI, or Vertex AI Agent Builder) and vector databases.
• Ability to communicate in English and German fluently in order to support client relationship management in Germany.

Preferred qualifications:

• Experience in financial services, and with the regulatory and operational clearing, settlement, or custody.
• Experience with Financial Services Institution (FSI0 regulatory practices and data residency, encryption at rest/transit (CMEK), and "explainable AI" requirements in banking.
• Experience with data modeling of relational, NoSQL, and data modeling (Star Schema, Data Vault, etc.).
• 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 product requirement document (PRD) and a working technical demo.
• Experience working in a high-maturity Developer Operations culture (trunk-based development, automated testing, blue/green deployments).

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. Make Google Cloud the preferred choice for customers by delivering the highest-value, industry relevant solutions.

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.

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 users) to identify high-impact AI use cases. Translate these into product requirement documents (PRDs), clearly defining critical user journeys (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 continuous integration (CI)/ continuous delivery (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.