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Snowflake is seeking a Principal Software Engineer for its Anti-Abuse team, a core function responsible for protecting the Snowflake platform and its customers from abuse and fraud. The Anti-Abuse team leads platform-wide abuse and fraud detection while designing and deploying proactive controls for Snowflake's highest-risk capabilities including Snowpark, Data Sharing, Cortex AI, and emerging cloud engineering challenges.
In this role, you will serve as the lead technical architect responsible for defining and driving the technical strategy for abuse prevention, detection, and response across the entire Snowflake ecosystem. You will define and drive the long-term technical vision for abuse and fraud detection, serving as the chief architect for platform-wide anti-abuse strategy. You will partner directly with product and engineering teams building Snowflake's newest and highest-risk surfaces to design and deploy robust anti-abuse controls from day one.
Key responsibilities include architecting and scaling high-throughput, low-latency telemetry pipelines and risk-scoring engines capable of analyzing millions of queries, sessions, and data transactions across multi-cloud environments (AWS, Azure, GCP). You will continuously model emerging abuse techniques including trial compute abuse, cryptocurrency mining, bot-driven account creation, credential stuffing, and illicit network traffic routing. You will design intelligent mitigation systems that automatically throttle, challenge, or isolate abusive workloads and malicious actors with near-zero false-positive impact on legitimate enterprise workloads.
You will also raise the technical bar across the engineering organization through mentorship of staff and senior engineers, and influence architectural standards across adjacent platform teams.
The Anti-Abuse team works at the intersection of platform security, distributed systems, and adversarial thinking. This is not a compliance checkbox role: you will architect real-time detection systems, embed native guardrails into new product primitives before they reach production, and partner directly with engineering leaders across the organization to anticipate threats.
REQUIREMENTS:
- 12+ years of software engineering experience in distributed systems, cloud platform infrastructure, or security engineering, with significant time dedicated to anti-abuse, fraud detection, platform trust, or threat mitigation
- Proven track record architecting mission-critical, large-scale distributed services in Java, C++, or Python
- Deep experience designing controls for code-execution runtimes, multi-tenant compute environments, cloud APIs, or data platforms (e.g., mitigating compute hijacking, sandbox escapes, abuse of serverless functions, or network egress abuse)
- Demonstrated ability to build streaming event processing, anomaly detection, behavioral heuristic engines, or graph-based syndicate detection systems at enterprise scale
- Strong intuition for attacker economics and mechanics, with experience modeling threat vectors across account lifecycles (signup, trial, payment, execution, sharing)
- Exceptional ability to partner with product managers, infrastructure teams, and security researchers to embed safety controls into high-velocity product roadmaps
- B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, Cybersecurity, or equivalent practical experience
BONUS:
- Experience building anti-abuse systems for multi-tenant cloud platforms or SaaS-at-scale environments
- Familiarity with AI/LLM abuse vectors (prompt injection, model extraction, automated content generation for fraud)
- Track record of 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 simultaneously
