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AI COE Analyst

Job in Foster City, San Mateo County, California, 94420, USA
Listing for: Visa
Full Time position
Listed on 2026-05-27
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Job Description

At Visa, AI is central to our vision for the future of payments and commerce. We are committed to building enterprise‑scale, responsible AI solutions that deliver measurable value for our clients, partners, and the global economy. The AI Center of Excellence (AI COE), part of the Global Data Office, is at the forefront of this mission – developing reusable AI/ML frameworks, enabling agentic AI workflows, and accelerating innovation across Visa’s data science community.

The AI COE operates as both an enterprise capability builder and an AI SWAT team, tackling high‑impact projects that address complex business challenges and create scalable, reusable solutions. From evaluating cutting‑edge AI methods to deploying reusable frameworks in production, our mission is to improve efficiency, adoption, and business outcomes across Visa’s global Data & AI ecosystem.

We are seeking an AI COE Analyst to contribute to technically complex AI initiatives – from research and prototyping through deployment – while advancing reusable AI capabilities and accelerating adoption across Visa.

The AI COE Analyst will:

  • Design, develop, and deploy advanced AI/ML methods and agentic AI workflows that address high-value challenges across Visa.
  • Contribute to the creation of reusable AI frameworks, components, and internal open-source assets for enterprise-wide adoption.
  • Evaluate emerging AI/ML techniques, benchmark performance, and validate business impact using real Visa datasets and use cases.

Support the end-to-end delivery of AI COE projects, including:

  • Identifying and refining problem statements with stakeholders
  • Prototyping advanced models, pipelines, and automation workflows
  • Building high-quality, reusable code assets
  • Ensuring production readiness and integration with enterprise systems
  • Developing technical documentation, metadata, and best practices for validated AI methods
  • Contributing to quality assurance through code reviews, prompt engineering support, model evaluation frameworks, and benchmark design
  • Ensuring compliance with governance, security, and Responsible AI standards in all AI COE outputs
  • Quantifying and communicating impact using KPIs such as model accuracy, workflow efficiency gains, adoption metrics, and business value delivered
  • Collaborating with data scientists, ML engineers, product teams, and global partners to embed AI COE solutions into enterprise workflows and maximize adoption
  • Staying current on the latest AI frameworks, agentic AI patterns, and LLM ecosystems, rapidly evaluating and prototyping new methods for potential enterprise use

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications

Basic Qualifications:

  • 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g., Masters, MBA, JD, MD, or PhD)

Preferred Qualifications:

  • 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g., Masters, MBA, JD, MD)
  • 2+ years of hands-on experience in AI/ML, data science, workflow automation, or applied machine learning research
  • Advanced degree in Computer Science, Data Science, Statistics, Business Analytics, Engineering, or a related quantitative field
  • Demonstrated experience delivering AI/ML models or agentic AI workflows in production or enterprise environments
  • Hands‑on expertise with PyTorch, Tensor Flow, scikit-learn, Hugging Face Transformers, or similar frameworks
  • Experience with agentic AI tooling (e.g., Lang Chain, Llama Index) and multi-step workflow automation
  • Strong data engineering foundations, including Python, SQL, Spark, Databricks, Airflow, Kafka, or ETL/ELT pipelines
  • Familiarity with enterprise data systems, APIs, and MLOps (CI/CD, model monitoring, containerization)
  • Ability to translate complex AI concepts into clear, actionable insights for technical and non-technical stakeholders
  • Understanding of AI governance, model evaluation, and Responsible AI practices
  • Experience working cross-functionally in a large, global organization
Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position…

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