Senior Engineer (fraud)

Apollo.io Apollo.io · Enterprise · United States · Engineering

Senior Engineer role focused on building and improving fraud detection and account security systems. This involves developing risk decisioning engines, APIs, and collaborating with Data Science and Fraud Operations to implement new models and detection strategies. The role requires strong backend engineering skills and experience with production systems, with a preference for fraud or security-adjacent experience.

What you'd actually do

  1. Lead the implementation and ongoing improvement of abuse detection services and customer account security features
  2. With assistance of technical leadership, implement a home-grown risk decision engine
  3. Build and maintain APIs to support extensible, low-latency risk decisioning
  4. Research and analyze abuse tools and attacker tactics to inform detection strategies
  5. Participate in fraud incident triage and lead development of mitigations and remediation

Skills

Required

  • 5+ years building production backend systems in a SaaS or similar environment
  • Experience designing scalable backend services
  • Proven track record of designing customer-first features
  • Ability to explore and validate ideas using imperfect or partially structured data
  • Strong foundation in secure system design and layered defenses
  • Comfortable presenting designs to both technical peers and senior stakeholders
  • Familiarity with common abuse vectors, evasion techniques, or scraping patterns
  • Strong ownership mindset and ability to prioritize effectively
  • Clear written and spoken English communication

Nice to have

  • exposure to risk or decisioning systems a plus
  • Fraud, trust & safety, or security-adjacent experience preferred

What the JD emphasized

  • build systems that protect our customers and business
  • modernize abuse detection logic
  • prototype and deploy new risk decisioning systems
  • build the technical foundation for new fraud decision models

Other signals

  • building the technical foundation for new fraud decision models
  • modernize abuse detection logic
  • prototype and deploy new risk decisioning systems