Staff Software Engineer

Visa Visa · Fintech · Austin, TX

Staff Software Engineer at Visa on the VAS Innovation & Learning team, focusing on full software development lifecycle for custom applications and SaaS solutions, including learning platforms. The role involves integrating Generative AI into learning products, leading modernization initiatives, and ensuring platforms remain industry-leading. Requires expertise in .NET, Azure, DevOps, and experience with AI/ML, Generative AI, and conversational AI solutions like RAG and NLP.

What you'd actually do

  1. Design and build complex features and services across .NET-based applications
  2. Contribute to automation, tooling, and GenAI adoption
  3. Contribute to modernization initiatives for Visa University, including: GenAI-driven learner support tools.
  4. Write clean, maintainable code following established architecture and code governance principles.
  5. Partner with product, security, and infrastructure teams

Skills

Required

  • 5+ 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, OR 8+ years of relevant work experience.
  • Expert in C#/.NET with strong full-stack development across modern web frameworks, APIs, and Azure cloud
  • Deep experience designing scalable, resilient enterprise systems and distributed architectures
  • Strong DevOps and CI/CD expertise, including containerization and release management
  • Proficient in monitoring, logging, and maintaining high-quality, maintainable codebases
  • Solid foundation in security, authentication, and secure development practices
  • Effective collaborator with strong communication skills across global, agile teams

Nice to have

  • Strong AI/ML and data engineering expertise, including model development and large-scale data processing
  • Experience building and integrating Generative AI and conversational AI solutions (RAG, NLP) into enterprise systems
  • Solid understanding of deep learning and neural network fundamentals
  • Advanced skills in concurrency, error handling, and enterprise-scale system design
  • Proficient in version control for both software and ML models, with a track record of embedding AI into distributed systems

What the JD emphasized

  • Generative AI
  • GenAI

Other signals

  • Integrate emerging technologies such as Generative AI into learning products
  • GenAI-driven learner support tools
  • Experience building and integrating Generative AI and conversational AI solutions (RAG, NLP) into enterprise systems