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Solutions Architect, Financial Services, Google Cloud

LinkedIn Google Atlanta, GA
Not Applicable Posted March 14, 2026 Job link
Responsibilities

On the Google Cloud team at Google, you'll act as a trusted technical advisor to executive stakeholders at major financial institutions, designing and deploying end-to-end AI and analytics solutions on GCP (including Vertex AI, Generative AI models, and BigQuery) for use cases like fraud detection, personalized banking, and automated regulatory reporting. You will lead migrations from legacy data warehouses to BigQuery, implement modern data governance frameworks that meet financial regulatory requirements, and build proofs-of-concept that demonstrate the value of Google’s AI tools. You’ll also collaborate with Business, Product Engineering, and Professional Services teams to align customer needs with the Google Cloud product roadmap and advocate for AI and analytics features.

Commitments

The application window will remain open until at least February 24, 2026, with the posting staying online based on business needs, which may extend before or after that date. By applying, you can indicate a preferred work location from Chicago, IL; Atlanta, GA; Austin, TX; Boulder, CO; or Addison, TX.

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Requirements
  • 5 years of experience in architectural design and deployment of cloud-based solutions, utilizing BigQuery for data warehousing and analytics.
  • Experience in implementing machine learning workflows or generative AI solutions using Vertex AI or similar cloud-native AI platforms.
  • Experience working within the Financial Services sector (e.g., banking, insurance, or capital markets).
  • Experience in customer-facing role advising stakeholders on data modernization strategies and the integration of AI into core business processes.
  • You will combine your technical mastery of Vertex AI, Gemini Enterprise, BigQuery and other Google Cloud offerings with an understanding of financial industry workflows.
Preferred Skills
  • Experience in systems design with ability to architect and explain data analytics pipelines and data flows.
  • Experience designing and deploying with one or more from the following technologies: TensorFlow, Spark ML, CNTK, Torch, Caffe, Scikit-learn.
  • Experience in a statistical programming language like R or Python and applied machine learning techniques (e.g., dimensionality reduction strategies, classification, and natural language processing frameworks).
  • Understanding of industry-specific data security or regulatory compliance requirements.
  • Excellent communication, presentation and problem-solving skills.
  • You will combine your technical mastery of Vertex AI, Gemini Enterprise, BigQuery and other Google Cloud offerings with an understanding of financial industry workflows.
Education
  • (Not required) – Bachelor's degree or equivalent practical experience.