Principal Software Engineer (Anti-Abuse)

Location: Bellevue, Washington, United States; hybrid

Salary: $264,000–$379,500 per year

Company

Snowflake provides a cloud data platform supporting data workloads, sharing, AI services, and multi-cloud infrastructure.

What you will do

• Define the long-term technical vision and architecture for abuse and fraud detection across the Snowflake platform.
• Partner with product and engineering teams to build anti-abuse controls for Snowpark, Data Sharing, Marketplace, and AI/LLM services.
• Architect high-throughput, low-latency telemetry pipelines and risk-scoring engines across AWS, Azure, and GCP.
• Model emerging threats including trial compute abuse, cryptocurrency mining, bot-driven account creation, credential stuffing, and illicit network routing.
• Design automated systems to throttle, challenge, or isolate abusive workloads while minimizing false positives.
• Mentor senior and staff engineers and influence architectural standards across platform teams.

Requirements

• 12+ years of software engineering experience in distributed systems, cloud infrastructure, or security engineering, including substantial anti-abuse, fraud detection, platform trust, or threat mitigation experience.
• Experience architecting large-scale distributed services with Java, C++, or Python.
• Experience designing controls for code-execution runtimes, multi-tenant compute, cloud APIs, or data platforms.
• Experience building streaming event processing, anomaly detection, behavioral heuristic, or graph-based detection systems at enterprise scale.
• Strong ability to collaborate with product managers, infrastructure teams, and security researchers.
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, Cybersecurity, or equivalent practical experience.

Nice to have

• Experience building anti-abuse systems for multi-tenant cloud or SaaS platforms.
• Familiarity with AI/LLM abuse vectors such as prompt injection, model extraction, and automated fraud content generation.
• Experience designing zero-trust or defense-in-depth architectures for compute runtimes.
• Published research or industry contributions in fraud detection, adversarial ML, or platform trust and safety.
• Experience operating detection and response systems across multiple cloud providers.

Culture & Benefits

• Work at the intersection of platform security, distributed systems, and adversarial thinking.
• Build real-time detection systems and native guardrails for a rapidly scaling cloud platform.
• Collaborate with engineering leaders across the organization on evolving security threats.
• Operate in an experimental, fast-moving environment focused on challenging conventional approaches.