SW Engineer- Sr. Consultant

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.

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 sophisticated processing networks, capable of handling more than 65k secure transactions per second across 80M merchants, 15k Financial Institutions, and billions of people globally.

As we evolve toward intelligent, AI-driven platforms, we are building the next generation of adaptive systems that combine large-scale distributed architectures with generative AI, semantic intelligence, and agentic workflows. Our teams are pioneering how intelligent software collaborates with humans to accelerate decision-making, automate complex workflows, and unlock new business capabilities across the enterprise.

The Opportunity

We are seeking a highly skilled Software Engineer to help architect and build intelligent, AI-native platforms that operate at global scale.

In this role, you will design and deliver full-stack systems that integrate large language models, retrieval-augmented generation (RAG), memory systems, semantic search, workflow orchestration, and secure enterprise data services. You will contribute to building agentic software systems capable of reasoning, planning, and executing multi-step tasks across complex business and technical environments.

You will partner closely with product leaders, AI researchers, data scientists, and platform engineers to transform emerging AI capabilities into secure, scalable, production-grade systems.

The Work Itself

• Design and implement distributed systems that embed generative AI and intelligent agents into enterprise workflows
• Architect end-to-end solutions spanning front-end experiences, backend services, orchestration layers, and data platforms
• Build scalable RAG pipelines, knowledge indexing systems, and context-aware memory frameworks
• Develop APIs and service layers that enable AI-driven task execution, workflow automation, and tool integration
• Ensure enterprise-grade security, observability, governance, and responsible AI practices in all solutions
• Contribute to reusable frameworks and internal standards for intelligent systems architecture
• Lead technical design discussions and influence architectural direction across multiple teams
• Mentor engineers and help establish best practices for AI-native application development
• Drive performance, scalability, and reliability for AI-enhanced services operating at global scale

Essential Functions

• Collaborate directly with product owners and business stakeholders to translate ambiguous AI use cases into scalable technical architectures
• Design robust, extensible solutions that integrate AI models, enterprise data systems, and internal platforms
• Provide technical leadership in implementing advanced architectural patterns for AI-enabled applications
• Lead end-to-end feature development across intelligent systems, from prototyping to production deployment
• Establish design standards for agent orchestration, prompt engineering, evaluation frameworks, and model observability
• Contribute to documentation, internal knowledge sharing, and platform adoption strategies

The Skills You Bring

AI-Native Builder:
Experience designing and deploying applications that integrate generative AI, large language models, or intelligent automation systems.

Architectural Depth:
Strong expertise in distributed systems design, API development, microservices, and cloud-native architectures.

Full Stack Engineering:
Experience building scalable backend services and intuitive front-end applications that deliver seamless human-AI interaction experiences.

Intelligent Systems Thinking:
Familiarity with concepts such as retrieval-augmented generation (RAG), semantic search, embeddings, context management, agent orchestration, or workflow automation.

Production Mindset:
Ability to operationalize AI systems with attention to security, compliance, latency, monitoring, and reliability.

Language Expertise:
Proficiency in one or more general-purpose languages (e.g., Java, C#, C++, Python) and modern web frameworks.

Challenge the Status Quo:
Comfort pushing boundaries beyond traditional system design to build adaptive, reasoning-driven software.

Partnership & Influence:
Experience collaborating across Product, Data Science, DevOps, Security, and Agile/Scrum teams to deliver cross-functional solutions.

Continuous Learner:
Curiosity and drive to explore emerging technologies in AI, orchestration frameworks, containerization, and cloud infrastructure.

We do not expect that any single candidate would fulfill all of these characteristics. We value engineers who are deeply strong in one or more dimensions - distributed systems, AI systems, or full stack engineering - and are excited to expand into others.

Basic Qualifications
•Master's degree in Math, Science, Engineering, or Computer Science, Information Systems or related field AND minimum six (6) years of experience in a directly related field.
OR
•Bachelor's degree in Math, Science, Engineering, or Computer Science, Information Systems or related field ANDminimum eight (8) years of experience in a directly related field.
OR
•Minimum eleven (11) years of directly related experience.

Preferred Qualifications
•Experience building or integrating generative AI applications, including large language models (LLMs), retrieval-augmented generation (RAG), embeddings, semantic search, or context-aware systems.
•Experience designing agentic workflows that support reasoning, multi-step task execution, tool usage, and orchestration across enterprise systems.
•Strong knowledge of front-end development (e.g., HTML, CSS, JavaScript, React, Angular) with experience building intuitive human–AI interaction experiences.
•Strong knowledge of back-end development (e.g., Python, Java, C++, C#) with experience building scalable APIs and microservices that integrate AI capabilities.
•Experience developing and consuming APIs for secure system-to-system integration, including integration with model providers, enterprise data services, and workflow engines.
•Experience designing data pipelines and working with structured and unstructured data sources, vector databases, and knowledge indexing systems.
•Familiarity with cloud-native architectures, containerization (Docker, Kubernetes), CI/CD pipelines, and deploying AI-enabled services in production environments.
•Experience implementing observability, evaluation frameworks, and performance monitoring for AI systems (e.g., prompt evaluation, model output quality, latency, reliability).
•Knowledge of security, compliance, and responsible AI practices when deploying AI-powered enterprise applications.
•Strong understanding of distributed systems, data structures, and system integration patterns required to combine independently developed components into cohesive, scalable platforms.

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.