About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
Team Description
Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients. VCA's core client segments include issuers, acquirers, merchants, fintechs, payment enablers and governments.
We are seeking a Senior AI Engineer to design, build, and deploy production-ready AI solutions that support strategic business initiatives. This role is focused on developing agentic AI architectures, LLM-powered applications, integrations, automation workflows, RAG systems, and scalable AI platforms.
This is a hands-on engineering role for someone with strong coding skills, practical AI expertise, and the ability to own solutions from concept through production. The ideal candidate is not only comfortable building AI prototypes, but also knows how to turn them into secure, maintainable, observable, and business-ready systems.
The successful candidate will work closely with business, technology, data, risk, compliance, and external partners to ensure AI solutions are delivered responsibly, effectively, and at scale.
Specific Responsibilities include:
- Design, develop, and deploy AI-powered applications using large language models, embeddings, retrieval systems, agentic workflows, APIs, and enterprise data sources.
- Build agentic AI architectures involving tool use, planning, memory, retrieval, structured outputs, orchestration, workflow automation, and multi-step reasoning.
- Develop backend services, APIs, and integrations that connect AI systems with internal platforms, third-party tools, databases, SaaS applications, and business workflows.
- Implement and optimize RAG pipelines, including document ingestion, chunking, embeddings, vector search, retrieval tuning, grounding, and response quality improvement.
- Design and implement robust AI architectures and solutions that support strategic business use cases, using scalable design principles and industry best practices.
- Maintain end-to-end technical ownership of AI solution implementation, from requirements analysis and architecture through development, deployment, monitoring, and continuous improvement.
- Ensure AI solutions are secure, compliant, maintainable, observable, and aligned with responsible AI practices.
- Build evaluation and monitoring capabilities to measure model performance, response quality, hallucination risk, retrieval accuracy, latency, cost, and business impact.
- Collaborate with business stakeholders to translate ambiguous needs into actionable technical requirements, solution designs, implementation plans, and working software.
- Support cross-functional alignment between business, engineering, data, risk, compliance, security, and vendor teams.
- Manage or coordinate outsourced resources and vendor relationships as needed, overseeing deliverables, timelines, dependencies, risks, and execution quality.
- Monitor, report, and communicate project progress clearly, including timelines, risks, mitigation plans, dependencies, and key decisions required from stakeholders.
- Drive continuous improvement of AI solutions by identifying opportunities to improve automation, user experience, operational efficiency, model performance, and business value.
- Stay current with emerging AI technologies, agentic frameworks, model capabilities, enterprise AI patterns, and responsible AI practices.
- Contribute to engineering standards, reusable AI patterns, documentation, and best practices for scalable AI solution delivery.
- Provide technical guidance to other engineers, vendors, or implementation partners as needed.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
Preferred Qualifications:
- 6 or more years of work experience with a Bachelor's Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
- 6–8+ years of software engineering experience
- Strong coding in Python and/or TypeScript/JavaScript
- Experience building production-grade systems, APIs, integrations, cloud apps
- Hands-on LLM/AI application development
- Experience with RAG, embeddings, agents, orchestration, vector databases
- Cloud experience (AWS, Azure, GCP)
- English + Spanish or Portuguese proficiency
- Agentic AI in production
- AI orchestration frameworks
- AI evaluation/monitoring tools
- Workflow automation / enterprise integrations
- Design safeguards for enterprise AI systems, including data privacy controls, access management, prompt-injection mitigation, human review workflows, auditability, and model behavior monitoring
- Experience with payments, fraud, risk, authorization, customer servicing, merchant operations, or financial data products is a plus
- Technical Skills & Professional Capabilities:
- The ideal candidate should be comfortable with several of the following:
- Strong engineering discipline: Writes clean, maintainable, testable, and production-ready code.
- AI Engineering & Architecture: LLM applications, RAG, agents, tool use, structured outputs, scalable solution design
- Software Engineering & Platforms: Python, TypeScript/JavaScript, APIs, backend services, cloud, containers, CI/CD
- Data & Integration: vector databases, SQL/NoSQL, OCR/document processing, ETL/ELT, enterprise system integration
- Execution & Ownership: autonomy, planning, delivery management, risk/dependency handling, vendor coordination
- Communication & Business Alignment: translating business needs into technical solutions, stakeholder communication, measurable business value
- Leadership & Continuous Improvement: technical guidance, reusable patterns, quality mindset, learning agility
Visa is an EEO Employer
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.