Solutions Architect, Digital Platforms, Google Cloud

In this role, you will be part of the Global Solutions and Consumer AI organization with Google Cloud. You will accelerate customer value and increase adoption by delivering innovative, repeatable, and enterprise-ready solutions focused on business value. You will make Google Cloud the preferred choice for customers by delivering the highest-value, industry relevant solutions.

As the Solution Architect, Financial Services, operating within the Innovation Delivery team, you will collaborate with clients to transform initial concepts into reality. You will design and architect solutions using blockchain, tokenization, and AI-driven automation to modernize traditional workflows for a strategic customer in the capital markets finance industry. Working at the heart of Financial Market Infrastructures (FMIs) including high-stakes clearing, settlement, and custody environments, you will identify where modern financial technology can drive systemic efficiency.

This role is for a problem solver, innovator, and builder. As a strong team player, you will work under the guidance of senior team members to architect solutions for customers. You will design functional prototypes including a scalable blockchain position-keeping service for tokenized instruments and a WalletNext service for AI agents usable across a broad base of GCP clients.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Germany: €148000 - €151000 (EUR) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Design and architect a scalable position-keeping service for blockchain networks, supporting internal and external tokenized, detokenized, and hybrid financial instruments for Next-Gen financial architecture.

Architect and oversee the development of the wallet service, enabling AI agents to seamlessly query real-time position data for customers.

Partner with client leads (business users) to create Product Requirement Documents (PRDs), clearly defining Critical User Journeys (CUJs) and success metrics.

Evaluate and integrate solutions with modern data foundations including relational databases, data lakehouses, and real-time streaming architectures ensuring data pipelines are optimized for AI retrieval, agentic workflows, and real-time financial insights.

Create clear technical guides to ensure a seamless hand-off from POC to engineering teams.

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 programming in Python, Go, or Java, and experience with design patterns, testing frameworks, and API contract design.

Experience in back-office clearance, trade reconciliation, and identifying or mitigating transaction settlement risks.

Experience designing and implementing Distributed Ledger Technology (DLT) solutions and smart contracts within regulated Financial Market Infrastructures (FMIs), including managing the lifecycle of tokenized assets.

Preferred qualifications:

Experience using AI tools to significantly increase personal coding velocity and code quality.

Experience in financial services, familiarity with the regulatory and operational rigors of clearing, settlement, or custody.

Proficient in BigQuery, Vertex AI, Dataflow, and Pub/Sub.

FSI regulatory knowledge for data residency, encryption at rest/transit (CMEK), and explainable AI requirements in banking.

Strong understanding of relational, NoSQL, and analytical data modeling (e.g., Star Schema, Data Vault, etc.).

Ability to independently drive the discovery phase, moving from a vague business problem to a structured PRD and a working technical demo.