(usa) Staff, Software Engineer - Fraud and Risk Platform

Walmart Walmart · Retail · SUNNYVALE TECH CORNERS BLDG 6 CA SUNNYVALE

Staff Software Engineer role focused on building and scaling intelligent systems for fraud and risk detection within Walmart's ecosystem. The role involves developing real-time decisioning platforms, entity resolution systems, and integrating AI/ML capabilities, including agentic systems, into production workflows in a high-scale, low-latency environment. Responsibilities include owning the software lifecycle, collaborating across teams, and driving engineering excellence.

What you'd actually do

  1. Develop platforms for real-time abuse detection (card testing, checkout fraud, signup abuse, offer exploitation)
  2. Integrate AI-driven workflows and agentic systems for fraud analysis
  3. Design, build, test, deploy, and operate services end-to-end
  4. Partner with Gateway teams for real-time decision integration
  5. Participate in design reviews and contribute to architecture decisions

Skills

Required

  • Strong experience building distributed systems and backend platforms at scale
  • Proficiency in one or more: Java, Python, JavaScript/TypeScript, or similar
  • Experience with real-time systems, event-driven architectures, and microservices
  • Experience working with or integrating ML models into production systems
  • Familiarity with ML concepts (classification, anomaly detection, ranking)
  • Understanding of data modeling, streaming systems, and low-latency architectures
  • Strong problem-solving skills and ability to deliver scalable solutions
  • Ability to collaborate effectively across engineering, product, and data science teams

Nice to have

  • Exposure to fraud, risk, identity systems, or abuse detection is a strong plus

What the JD emphasized

  • agentic AI-driven fraud analysis
  • low-latency, high-scale environment
  • real-time decisioning
  • productionize ML models
  • agentic systems

Other signals

  • productionize ML models
  • agentic AI-driven fraud analysis
  • low-latency, high-scale environment
  • real-time decisioning