Senior Security Architect, Applied Field Engineering (AFE)

Key Responsibilities

Field Engineering & Security Architecture

• Drive strategic engagements focused on Security Architecture, ensuring robust foundations across Identity, Data, and Infrastructure for applications built on Snowflake.
• Support customer strategy for secure AI adoption, leveraging Snowflake Cortex to bring state-of-the-art LLMs directly to customer data within a secure environment.
• Architect trusted Agentic AI frameworks where Cortex Agents operate within governed boundaries, autonomously orchestrating tasks while inheriting Snowflake's native security perimeter.
• Deploy Cortex Guard and AI Observability to filter harmful content and provide transparent, explainable AI interactions through rigorous monitoring and tracing.
• Ensure AI governance by enforcing Role-Based Access Control (RBAC) and data masking across all AI-driven insights and automated actions.
• Deliver workshops and hands-on engagements to transition customers from legacy infrastructure to advanced SIEM Augmentation, Log Ingestion (Otel/Logs into Snowflake), and Cybersecurity Data Lake.
• Build repeatable reference architectures and frameworks for Identity (IAM), Data Governance, Row-Level Security, and Encryption to accelerate well-architected deployments.
• Guide customers through end-to-end journeys for BC/DR (Business Continuity/Disaster Recovery), including multi-region deployment patterns and measurable recovery outcomes.
• Drive the creation of relevant technical content and tooling to showcase security best practices, accelerate new use case deployments, and adoption of new platform functionality.
• Influence product roadmaps by serving as the Voice of the Field to Snowflake's product and engineering teams, translating customer needs into actionable feedback.

Core Experience

• 5+ years of industry experience in Data, Security, Networking, Infrastructure or AI Engineering.
• Strong technical communications skills with the ability to deliver compelling demos, whiteboard sessions, and presentations to both technical and business stakeholders.
• Customer-facing skills: The ability to act as a trusted advisor and establish credibility with senior leadership and enterprise architects.

Relevant Security Skill Sets

• Generative AI Security: Deep understanding of LLM security risks (e.g., prompt injection, data leakage) and mitigation strategies using tools like Cortex Guard.
• Agentic AI Governance: Expertise in governing Autonomous Agents, ensuring "Human-in-the-loop" controls and auditability for agent-driven actions.
• Data Privacy for AI: Mastery of techniques like Differential Privacy, Data Masking, and Secure Sandboxing to protect sensitive training and inference data.
• Platform Observability: Proficiency in observability techniques including logging, monitoring, and distributed tracing on a platform level.
• Identity and Access Management (IAM): Expertise in modern authentication/authorization protocols (OAuth 2.0, OpenID Connect) and implementing robust Role-Based Access Control (RBAC) models across cloud and on-premises environments.
• Secure Networking: Hands-on expertise in securing cloud and hybrid network architectures, including micro-segmentation, zero-trust principles, and secure deployment of services like Apache NiFi.
• Programming: Hands-on expertise with SQL, Python, and APIs.
• Container and Kubernetes Security: Proficiency in securing the container lifecycle, from build (image scanning) to runtime (Pod Security Standards, network policies, service mesh), and managing secrets within Kubernetes.
• Governance, Risk, and Compliance (GRC): Strong background in aligning security programs with regulatory frameworks (e.g., SOC 2, HIPAA, GDPR) and managing security risk through continuous monitoring and auditing.

Compliance & Standards (nice to have)

• AI Regulatory Knowledge: Understanding of emerging AI regulations (e.g., EU AI Act) and their impact on enterprise data strategy.
• Trust Certifications: Familiarity with how Snowflake’s AI Trust Center maps to SOC2, HIPAA, and HITRUST requirements for AI/ML workloads.
• Industry Certifications: CISSP