Security Architect, Applied Field Engineering
Snowflake · US-CA-Menlo Park
About this role
## Security Architect — Applied Field Engineering (AFE) At Snowflake, we’re powering the era of the agentic enterprise. We’re looking for AI-native thinkers who treat AI as a high-trust collaborator and thrive in fast-moving, experimental environments. As a **Senior Security Architect** on the **Applied Field Engineering (AFE)** team, you’ll drive strategic customer engagements and build prescriptive security frameworks for the modern era—helping customers transition from legacy, siloed security tools to a unified **Security Data Architecture** while maintaining a world-class security posture. --- ## Key Responsibilities ### Field Engineering & Security Architecture - Lead strategic engagements focused on **Security Architecture** 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 to customer data in a secure environment. - Architect **trusted agentic AI frameworks** where Cortex Agents operate within governed boundaries, autonomously orchestrating tasks while inheriting Snowflake’s security perimeter. - Deploy **Cortex Guard** and **AI Observability** for harmful-content filtering and transparent, explainable AI interactions via monitoring and tracing. - Ensure **AI governance** through **RBAC** and **data masking** across AI-driven insights and automated actions. ### Modern Security Operations (SecOps) - Deliver workshops and hands-on engagements to transition customers from legacy infrastructure to: - **SIEM Augmentation** - **Log ingestion** (Otel/Logs into Snowflake) - **Cybersecurity Data Lake** ### Governance, Identity, Resilience & Compliance - Build repeatable reference architectures for **IAM**, **Data Governance**, **Row-Level Security**, and **Encryption**. - Guide end-to-end journeys for **BC/DR** (Business Continuity/Disaster Recovery), including multi-region deployment patterns and measurable recovery outcomes. ### Tooling, Content & Voice of the Field - Create technical content and tooling to showcase security best practices and accelerate new use case deployments. - Serve as the **Voice of the Field**—translating customer needs into actionable feedback for product and engineering teams. --- ## Core Experience - **5+ years** of experience in Data, Security, Networking, Infrastructure, or AI Engineering. - Strong technical communication skills (demos, whiteboarding, presentations) for both technical and business stakeholders. - Ability to act as a trusted advisor to senior leadership and enterprise architects. --- ## Relevant Security Skill Sets - **Generative AI Security**: LLM risks (e.g., prompt injection, data leakage) and mitigations (e.g., Cortex Guard). - **Agentic AI Governance**: Governing autonomous agents with **human-in-the-loop** controls and auditability. - **Data Privacy for AI**: Differential privacy, data masking, secure sandboxing. - **Platform Observability**: Logging, monitoring, distributed tracing. - **IAM**: OAuth 2.0, OpenID Connect, and RBAC models across cloud/on-prem. - **Secure Networking**: micro-segmentation, zero-trust, secure hybrid architectures. - **Programming**: SQL, Python, and APIs. - **Container & Kubernetes Security**: image scanning, runtime controls (Pod Security Standards, network policies, service mesh), and Kubernetes secrets. - **GRC**: Aligning security programs to frameworks such as **SOC 2**, **HIPAA**, **GD
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