Staff Software Engineer -ai & Middleware Automation

Visa Visa · Fintech · Austin, TX

Staff Software Engineer role focused on building agentic AI and automation frameworks for middleware reliability at Visa. The role involves designing and developing intelligent systems using AI/ML and LLM frameworks, integrating AI into reliability workflows, and leading production excellence. It requires strong software engineering skills, experience with cloud platforms, DevOps tools, and a curiosity for GenAI.

What you'd actually do

  1. Design and develop middleware reliability solutions with limited guidance — translating business and technical requirements into system designs that scale.
  2. Build intelligent automation systems leveraging AI/ML and LLM frameworks (LangChain, LangGraph, RAG pipelines).
  3. Respond to complex incidents with customer or business impact — troubleshoot root causes, deploy fixes, and recommend solutions to prevent recurrence.
  4. Lead junior engineers in understanding requirements, coding standards, and engineering practices.

Skills

Required

  • Python
  • Java
  • Go
  • Agentic AI
  • software engineering
  • systems design
  • data structures
  • algorithms
  • software development lifecycle
  • DevOps tools
  • CI/CD pipelines
  • cloud platforms
  • containerization
  • monitoring/observability tools
  • debugging
  • troubleshooting
  • root cause analysis
  • mentoring engineers
  • leading code reviews
  • secure coding practices
  • middleware experience

Nice to have

  • LangChain
  • LangGraph
  • RAG pipelines
  • Kubernetes
  • AWS
  • GCP
  • Azure
  • Prometheus
  • Splunk
  • Grafana
  • GenAI
  • Tomcat
  • Apache
  • Spring Boot
  • JBoss
  • IBM MQ
  • IBM DataPower
  • Hazelcast
  • Kafka
  • Flink
  • SQS
  • Open-source contributions
  • public engineering portfolio

What the JD emphasized

  • agentic AI
  • middleware reliability
  • AI/ML
  • LLM frameworks
  • production-grade automation
  • intelligent systems
  • reliability engineering workflows
  • eliminate toil
  • prevent recurring incidents
  • customer or business impact
  • incident response
  • advanced monitoring and observability
  • systemic risks
  • coding standards
  • engineering practices
  • constructive technical feedback
  • tooling, automation, and reliability practices
  • design learnings
  • investigative findings
  • AI agents into production systems
  • CORE TECHNOLOGIES: Python | Java | Go | Agentic AI

Other signals

  • agentic AI
  • automation frameworks
  • self-healing platforms
  • LLM frameworks
  • RAG pipelines