Description
At Snowflake, we are powering the era of the agentic enterprise.
Enterprises are modernizing data platforms at an exponential rate to meet demands for innovation, specifically with the rise of Generative and Agentic AI.
As a Senior Security Architect on the Applied Field Engineering team, you will drive strategic customer engagements and build the prescriptive frameworks required for the modern era.
Key Responsibilities
- FIELD ENGINEERING & SECURITY ARCHITECTURE
- Drive strategic engagements focused on the 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.
- Modern Security Operations (SecOps): 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.
- Governance & Identity: Build repeatable reference architectures and frameworks for Identity (IAM), Data Governance, Row-Level Security, and Encryption to accelerate well-architected deployments.
- Resilience & Compliance: Guide customers through end-to-end journeys for BC/DR (Business Continuity/Disaster Recovery), including multi-region deployment patterns and measurable recovery outcomes.
- Tooling and Content: 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.
- Voice of the Field: 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
- Communication Skills: 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.