Staff Software Engineer - Python, AI/ML, Cloud, GenAI

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.

Join Visa’s Technology Organization, a dynamic community of problem solvers and innovators dedicated to redefining the future of commerce. We manage one of the world’s most advanced processing networks, handling over 65,000 secure transactions per second across 80 million merchants, 15,000 financial institutions, and billions of individuals.

In this senior role, you will drive the development of generative AI (GenAI) solutions. You will provide technical leadership across teams to define and enforce best practices, bring a product-driven mindset, and ensure our GenAI platforms and applications are robust, scalable, and aligned with business needs. This role requires a hands-on leader with a passion for AI innovation, strong mentorship skills, and deep expertise in Python, LangChain, Azure cloud services, and vector databases.

Key Responsibilities:

Technical Architecture & System Design:

• Work with architects to design and implement core components of GenAI systems, including LLM agent orchestration, retrieval-augmented generation (RAG) pipelines, prompt-engineering frameworks, and model fine-tuning workflows. Make sound architectural decisions, evaluate alternative approaches, and ensure solutions meet enterprise expectations for performance, reliability, scalability, and security.

Hands-on Solution Development:

• Lead end-to-end development of GenAI solutions from concept through production. Prototype and build critical components in Python, integrate large language models and frameworks such as LangChain, and operationalize embeddings, vector stores, and RAG pipelines. Ensure AI systems address real-world use cases and deliver measurable business impact.

Cross-Functional Collaboration:

• Drive cross-team alignment, influence architectural decisions across departments, and champion adoption of AI in high-value use cases. Ensure GenAI initiatives remain aligned with the broader enterprise technology strategy.

Technical Leadership & Mentorship:

• Provide senior technical leadership and mentorship to engineers at all levels. Conduct code reviews, support pair programming, guide architectural discussions, and lead micro-teams or pods to deliver complex features. Foster a collaborative, inclusive, and learning-oriented engineering culture.

Engineering Excellence:

• Establish and enforce coding standards, rigorous testing practices, and high-quality documentation. Drive consistent adoption of CI/CD pipelines and strengthen secure coding practices. Maintain high test coverage and ensure solutions meet enterprise expectations for security, reliability, performance, and compliance. Apply strong engineering fundamentals end-to-end by writing clean, maintainable, well-tested code; following modern design patterns; implementing robust unit, integration, and functional tests; and ensuring operational reliability through monitoring, observability, and resilient error handling. Review code developed by other engineers and provide actionable feedback to ensure adherence to best practices.

Agile Project Leadership:

• Lead and actively participate in Agile/Scrum ceremonies, including sprint planning, backlog refinement, and retrospectives. Manage work through Jira, optimize deployments via CI/CD pipelines (for example, Jenkins), remove execution blockers, and maintain alignment across teams to ensure timely delivery of GenAI features.

Product Mindset & Innovation:

• Identify opportunities where GenAI can create user value or improve internal workflows. Propose, design, and deliver innovative AI-driven features and enhancements. Anticipate future business needs, develop proof-of-concepts, and transition them into scalable, production-ready solutions while balancing rapid experimentation with sound architecture.

Responsible AI & Governance:

• Ensure all GenAI solutions adhere to responsible AI principles. Integrate privacy, fairness, safety, and security considerations throughout the development lifecycle. Partner with governance, legal, and security teams to establish guardrails and standard practices for the safe enterprise deployment of large language models.

Continuous Learning & Thought Leadership:

• Stay current with emerging advancements in AI and machine learning, including new LLMs, vector database technologies, open-source frameworks, and cloud AI capabilities. Evaluate and adopt techniques that strengthen the platform, and represent the GenAI team in knowledge-sharing forums while communicating innovations to broader engineering groups and leadership.

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

Experience:

• 7-10 years of software development experience, including substantial hands-on work in AI/ML or GenAI projects (preferably 2–3 years focused on building applications with LLMs or related technologies).
• Prior experience as a technical lead or senior engineer is expected, with a demonstrated ability to guide teams through complex, ambiguous projects.
• Bachelor’s degree in Computer Science, Engineering, or a related field. A Master’s degree or PhD in AI/ML or a related specialization is a plus, or equivalent hands-on experience building AI systems at scale.

Technical Expertise:

• In-depth understanding of large language models and generative AI techniques, including prompt engineering, model fine-tuning, embeddings, and retrieval-augmented generation for knowledge-based systems. Proven ability to design and build systems that incorporate LLMs, agent workflows, or NLP services. Experience building AI agents capable of multi-step reasoning or tool use is a strong plus.
•  Advanced proficiency in Python for AI/ML development, with familiarity in Java or other object-oriented languages. Experience using GenAI frameworks and libraries—such as LangChain, CrewAI, or OpenAI-compatible APIs—to develop and integrate AI capabilities. Strong understanding of data structures and algorithms, with the ability to write efficient, production-quality code.

 

• Hands-on experience with cloud platforms (Azure, AWS, or GCP) and deploying AI solutions at scale. Knowledge of containerization and microservices architectures is beneficial. Experience working with vector databases or similar technologies for embedding storage and semantic search is required.

 

• Strong understanding of Agile methodologies and experience working in Scrum teams. Proficiency with tools such as Jira for project tracking and CI/CD pipelines (for example, Jenkins and Git-based workflows) for automated build and deployment. Comfort with test-driven development, continuous integration, and continuous delivery practices is expected.

 

• Excellent leadership and communication skills, with a track record of mentoring engineers and influencing teams beyond direct ownership. Ability to set technical direction, gain stakeholder buy-in, and clearly communicate complex technical concepts to product managers, partners, and senior executives.

 

• Demonstrated ability to tackle ambiguous problems and decompose them into actionable plans. A forward-looking mindset to anticipate challenges and opportunities in the GenAI space, balancing short-term delivery with long-term architectural and strategic investments.

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.