Staff Software Engineer

Visa•Bellevue, WA

12d•$131,600 - $210,300•Hybrid

About The Position

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce. We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people. While working with us you’ll get to work on complex distributed systems and solve massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms. The Opportunity: We are seeking a Staff Software Engineer (Backend) to design, build, and operate scalable, high‑performance backend systems, including services enhanced with Generative AI and agent‑based capabilities. In this role, you will work closely with senior engineers, product partners, and platform teams to deliver reliable microservices that power business‑critical applications. This is a hands‑on senior individual contributor role. You will contribute to technical design, mentor engineers, perform code reviews, and help integrate AI‑powered features—such as LLM‑backed services, agent workflows, and context‑aware systems—into production environments. The ideal candidate combines deep Java backend expertise with practical experience applying modern AI tools and techniques to real‑world software development.

Requirements

2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience
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)
Master’s degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of directly related experience, or Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of directly related experience, or 8+ years of equivalent professional experience.
5+ years of experience with Core Java and RESTful web service development.
3+ years of experience with Spring Framework / Spring Boot and build tools such as Maven.
Strong experience with event‑driven and reactive systems using Kafka.
Strong knowledge of Spring Data, JPA, JDBC, and relational database access.
Solid understanding of object‑oriented design, design patterns, concurrency, and multithreading.
Experience with CI/CD pipelines and cloud‑native deployments using Jenkins, Docker, and Kubernetes.
Familiarity with security scanning tools such as Checkmarx, Qualys, Aqua, and remediation best practices.
Strong SQL optimization skills; stored procedure experience is a plus.
Experience using ETL tools such as Clover DX for data import/export workflows.
Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG implementations.
Exposure to Python‑based services (FastAPI, Flask) in AI‑enabled systems.
Experience with API automation frameworks (Rest Assured, TestNG, JUnit, Jasmine, Jest).
Prior experience with AI/ML‑enabled systems in production environments.
Experience practicing test‑driven development (TDD).
Ability to design, understand, and author APIs.
Hands‑on experience integrating LLMs into backend applications.
Practical experience with prompt engineering and context management, including memory handling.
Familiarity with context engineering concepts, such as memory banks, session state, and retrieval layers.
Experience implementing or consuming MCP‑based or MCP‑inspired interfaces for AI tool and context integration.
Experience integrating AI agents into backend services or products, beyond experimentation or prototypes.
Demonstrated professional use of AI coding assistants (e.g., Claude, GitHub Copilot).

Nice To Haves

We do not expect that any single candidate would fulfill all of these characteristics. For instance, we have exciting team members who are really focused on building scalable systems but didn’t work with payments technology or web applications before joining Visa.

Responsibilities

Design, develop, test, and document scalable backend services using Java, Spring Boot, Kafka, and MySQL.
Build and maintain microservice‑based, multi‑tier applications that meet performance, reliability, and security requirements.
Develop RESTful APIs and event‑driven services that integrate cleanly with downstream systems.
Apply engineering standards, processes, and best practices throughout the software development lifecycle (SDLC).
Develop complex database queries and resolve defects in existing codebases.
Contribute to deployment procedures, environment configuration, and release readiness.
Produce highly available, high‑performance services capable of scaling under load.
Apply context engineering techniques, including use of memory banks, conversation state, and external knowledge sources, to improve relevance and consistency of AI‑powered features.
Design and maintain prompt engineering strategies to ensure reliable, secure, and high‑quality LLM responses across backend services.
Implement and integrate Model Context Protocol (MCP) patterns to enable structured tool access, context sharing, and interoperability between AI agents and backend APIs.
Integrate AI agents into production applications, enabling task automation, decision support, or intelligent workflows within backend services.
Leverage AI‑assisted development tools (e.g., Claude, GitHub Copilot, or similar) in day‑to‑day coding activities to improve development velocity, code quality, and maintainability.
Establish best practices for human‑in‑the‑loop workflows, fallback handling, and observability for AI‑driven features.
Design and support distributed, fault‑tolerant systems using event‑driven and asynchronous patterns.
Contribute to CI/CD pipelines and cloud‑native deployments using Docker, Kubernetes, and related tooling.
Support monitoring, logging, and alerting to ensure system health and operational excellence.
Participate in troubleshooting production issues and driving continuous system improvements.
Perform thorough code and design reviews to maintain high engineering standards.
Mentor junior and mid‑level engineers through technical guidance and example.
Collaborate with cross‑functional partners to preserve business goals and technical requirements.
Contribute to shared libraries, patterns, and engineering documentation.