Staff, Software Engineer

Walmart Walmart · Retail · Sunnyvale, CA

Staff Software Engineer to lead design and development of scalable distributed systems for Walmart's Marketplace and Seller experiences, with a focus on integrating GenAI capabilities into production systems.

What you'd actually do

  1. Lead architecture and design of scalable distributed systems across multiple services, ensuring high performance, reliability, and extensibility at scale.
  2. Drive complex, cross-team initiatives end-to-end, aligning stakeholders across Product, Engineering, and platform teams to deliver cohesive solutions.
  3. Build and integrate GenAI-driven capabilities into production systems, enabling intelligent automation and improved user experiences.
  4. Own technical direction and decision-making, including system design (HLD/LLD), trade-offs, and long-term platform strategy.
  5. Mentor engineers and elevate engineering standards, driving best practices in code quality, testing, observability, and operational excellence.

Skills

Required

  • System design
  • Distributed systems expertise
  • Technical leadership
  • Ownership
  • Cross-team collaboration
  • Stakeholder management
  • Problem-solving in ambiguous environments
  • Experience with modern technologies including GenAI and scalable platforms

Nice to have

  • GenAI
  • scalable platforms
  • event-driven systems

What the JD emphasized

  • GenAI-driven capabilities
  • GenAI capabilities
  • scalable distributed systems
  • system architecture
  • distributed computing
  • platform design
  • high-throughput, real-time workloads
  • intelligent automation
  • enhanced user experiences
  • robust technical solutions
  • stakeholder management
  • navigate ambiguity
  • influence across teams
  • cohesive, end-to-end systems
  • platform-level architecture
  • scalability, extensibility, and long-term sustainability

Other signals

  • integrating GenAI capabilities into production systems
  • building and scaling GenAI-driven capabilities
  • handling high-throughput, real-time workloads