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
Visa’s Technology Organization is a community of problem solvers and innovators, reshaping the future of commerce. We operate one of the world’s most advanced payment processing networks, enabling secure, reliable, and scalable transactions across millions of merchants, financial institutions, and consumers globally.
Our teams build and operate complex distributed systems at massive scale, solving challenges across payment flows, real-time data processing, cybersecurity, and next-generation digital platforms.
Within this, Value Added Services (VAS) – Digital Marketing is a key growth area for Visa, focused on building differentiated, data-driven solutions that extend the value of the Visa network beyond payments.
About the Team:
You will join a high-performing engineering team building GenAI-powered platforms and applications that enable innovation across Visa’s technology ecosystem.
The team focuses on:
- Developing intelligent, AI-driven applications powered by large language models
- Integrating generative AI capabilities into enterprise platforms and workflows
- Building scalable systems that combine AI, data, and distributed architectures
- Enabling automation, developer productivity, and intelligent decision-making
While these capabilities rely on strong data foundations, the primary focus is on applying AI and generative AI to solve real-world business problems at scale, with enterprise-grade security and reliability.
Job Summary:
Staff Data Engineers are expert problem-solvers, builders, and technical leaders who design and evolve platforms powering next-generation AI and data-driven applications. In this role, you will work extensively hands‑on with code, data, and modern technologies to deliver secure, scalable, and high-performance systems that drive business outcomes.
You will play a key role in developing GenAI-powered applications and platforms, including integrating with leading large language models such as OpenAI and Anthropic, and enabling their safe, scalable, and efficient use in enterprise environments.
You will independently understand data ecosystems, system design patterns, and security, privacy, and governance requirements, applying this knowledge to design robust and production‑ready solutions. You will translate complex business requirements into scalable architectures and guide implementation across the team.
This role requires strong expertise across backend engineering, data platforms, microservices, and real‑time distributed systems, along with the ability to influence engineering practices and drive high standards across teams.
All roles require digital fluency, including hands‑on experience or familiarity with Generative AI tools (e.g., Claude Code, Cline, Codex, and GitHub Copilot) to enhance developer productivity and enable intelligent engineering workflows.
Key Responsibilities:
- Act as a key technical contributor in stakeholder discussions to clarify requirements and drive architecture and design decisions
- Design and deliver scalable, resilient platforms and services supporting AI/GenAI applications and data‑driven systems
- Translate functional requirements into end‑to‑end system architectures, leveraging established design patterns
- Build and integrate applications with large language model providers such as OpenAI and Anthropic
- Design and implement GenAI workflows, including prompt orchestration, context handling, and system integration layers
- Lead development of microservices, APIs, and platform components supporting distributed systems
- Build and optimize real‑time data streaming and event‑driven architectures for high‑throughput applications
- Implement extensible, maintainable, and reusable code following best practices, security standards, and coding guidelines
- Take end‑to‑end ownership of data products, platform components, or services, including reliability, scalability, and maintainability
- Drive code reviews, mentor engineers, and guide teams on system design, coding practices, and performance optimization
- Build tools and automation to improve data processing, deployment, monitoring, and platform operations
- Ensure adherence to data management principles, governance, security, and compliance requirements
- Identify and address technical debt, and continuously improve system design and performance
- Lead troubleshooting of complex issues across distributed systems and drive root cause resolution
- Support platform upgrades, scaling initiatives, and security remediation activities
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 5+ years of relevant work experience with a Bachelor's degree, or 2+ years with an advanced degree, or 8+ years of relevant work experience
- Strong core programming skills in Java, Python, or similar languages, with ability to write scalable, maintainable, and high‑quality code
- Experience designing and implementing data pipelines, distributed systems, and large‑scale data processing jobs
- Experience building and operating microservices‑based architectures and APIs
- Experience working with real‑time data streaming or event‑driven systems
- Experience developing unit, integration, and end‑to‑end tests with a strong focus on automation
- Experience building and maintaining CI/CD pipelines and deploying applications using containerization and orchestration tools
- Experience working with cloud platforms such as AWS, including building and operating scalable, cloud‑native applications
- Experience monitoring applications in production and troubleshooting issues using observability and logging tools
- Experience integrating AI/ML or Generative AI services into applications, including working with LLM‑based systems
- Experience collecting and analyzing metrics to drive system optimization, performance, and reliability improvements
- Experience collaborating with cross‑functional stakeholders to clarify requirements and deliver robust technical solutions
- Experience applying secure coding practices and complying with enterprise security and regulatory standards
Preferred Qualifications:
- 6+ years of work experience with a Bachelor’s degree or 4+ years with an advanced degree
- Hands‑on experience building applications using LLM providers such as OpenAI, Anthropic, or similar platforms
- Experience designing and implementing GenAI workflows, including prompt design, context management, and orchestration patterns
- Experience with data and distributed technologies (Kafka)
- Experience building and operating high‑throughput, low‑latency real‑time systems
- Experience working with advanced AWS services for large‑scale systems
- Strong experience in building, deploying, and operating production‑grade systems at scale
- Experience mentoring engineers and driving engineering best practices across teams
- Ability to write clear, concise technical documentation and architecture designs
- Experience staying current with emerging trends in AI, GenAI, cloud platforms, and distributed systems, and applying them to real‑world problems
AI Engineering:
- Familiarity with concepts such as:Prompt engineeringSystem prompts and instruction designRetrieval‑augmented generationVector searchEmbeddingsTool callingFunction orchestrationContext managementAgent memoryEvaluation datasetsModel benchmarkingFeedback loopsA2A and MCP Protocols
- Experience with agentic AI frameworks or tools such as:LangChainLangGraphModel Context Protocol ServersSpring AIOpenAI and Anthropic SDKsVector databasesKnowledge graphsModel evaluation frameworks
- Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost.
- Experience using commercial or open‑source AI models and APIs.
- Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement.
Software Engineering:
- Strong programming ability in one or more languages such as:PythonTypeScript / Node.jsGoJava
- Experience building backend services, APIs, data pipelines, integrations, or cloud‑native applications.
- Familiarity with web applications, distributed systems, databases, CI/CD pipelines, logging, monitoring, and automated testing.
- Ability to write clean, maintainable, secure, and production‑ready code.
- Experience participating in design reviews, code reviews, and production troubleshooting.
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.