Senior Software Engineer (AI Security)

Location: Hybrid in Bellevue, Washington or Menlo Park, California, United States

Salary: $200K–$287.5K annually

Company

Snowflake provides a cloud-based Data Cloud platform and is building security, identity, infrastructure, and customer trust capabilities for secure data and AI workloads.

What you will do

• Design and implement AI security capabilities, including audited agent workflows, MCP security, agent identity frameworks, and administrative guardrails.
• Build identity and access management systems covering authentication, SSO, MFA, OAuth/OIDC, SAML, SCIM, and fine-grained RBAC.
• Develop security infrastructure for secrets, keys, service identity, and end-to-end encryption in a multi-cloud environment.
• Build tooling for security policy definition, monitoring, enforcement, violation detection, and secure-by-default automation.
• Extend Trust Center platform components, posture assessments, behavioral analytics, and PII attribution capabilities.
• Design secure network architectures, participate in reviews and on-call rotations, and defend against ransomware and data exfiltration.

Requirements

• 5+ years of experience designing, building, and operating large-scale distributed systems in production cloud environments.
• Strong knowledge of computer science, data structures, algorithms, systems design, and distributed computing.
• Proficiency in one or more of Java, C++, Python, Golang, or Rust, plus solid SQL skills.
• Experience operating production services with strong availability, reliability, and observability standards.
• Bachelor’s degree in Computer Science, Computer Engineering, or a related discipline, or equivalent practical experience.
• Ability to collaborate across engineering, product management, and design teams.

Nice to have

• Knowledge of SAML, SCIM, OAuth, OIDC, federation, MFA, or RBAC.
• Experience with secrets management, key management, service identity, authentication, or authorization.
• Background in database internals, query engines, data platforms, machine learning, anomaly detection, or behavioral analytics.
• Experience with developer platforms, SDKs, multi-tenant extensibility frameworks, Kubernetes, AWS, Azure, or GCP.

Culture & Benefits

• Work in security, identity, infrastructure, and customer trust layers of a large-scale data platform.
• Collaborative, low-ego engineering culture focused on craft, curiosity, and experimentation.
• High standards for code quality, reliability, observability, and technical decision-making.
• Opportunity to define security capabilities for the emerging agentic enterprise.