Staff Software Engineer

Visa Visa · Fintech · Austin, TX

Staff Software Engineer at Visa's VAS Innovation team, focusing on developing cutting-edge solutions leveraging generative AI and modern integration patterns. The role involves designing, developing, and implementing innovative software solutions, collaborating with cross-functional teams, and modernizing the VAS platform. Experience with Generative AI applications, conversational AI, RAG architectures, fine-tuning AI models, and MLOps is preferred.

What you'd actually do

  1. Engage in the design, development, and implementation of innovative software solutions, including generative AI and modern integration patterns. Contribute to a culture of innovation by actively exploring and applying new ideas and technologies.
  2. Collaborate with cross-functional teams to develop and deliver complex projects that integrate emerging technologies with our existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and other Product Development teams to build comprehensive solutions.
  3. Develop solutions with a client-centric mindset, ensuring that the VAS platform delivers exceptional value and innovation. Engage with client feedback to refine and improve our offerings.
  4. Contribute to the design and development of APIs that enhance the integration of our Value-Added Services applications, platforms, and solutions.
  5. Participate in the advancement of our modernization roadmap by adopting best-in-class technology solutions for our core platform, expanding our market reach and client base.

Skills

Required

  • Java
  • Python
  • API development
  • integration development
  • software development best practices
  • troubleshooting
  • root-cause analysis
  • application design
  • large components for enterprise projects
  • version control
  • CI/CD pipelines

Nice to have

  • C++
  • C#
  • ReactJS
  • Angular
  • NodeJS
  • Docker
  • Jenkins
  • Kubernetes
  • multi-threading
  • concurrency
  • error-handling
  • MLOps
  • Deep Learning
  • Stream Computing
  • model compression techniques
  • transfer learning
  • robustness issues in AI systems
  • deep learning basics
  • neural network architectures
  • training procedures

What the JD emphasized

  • generative AI
  • conversational AI
  • RAG architectures
  • fine-tuning AI models

Other signals

  • generative AI
  • conversational AI
  • RAG architectures
  • fine-tuning AI models
  • MLOps