Senior Security Architect, Applied Field Engineering (AFE)
Application analysis
Senior Security Architect, Applied Field Engineering (AFE) at Snowflake is a forward deployed cloud data warehouse role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Forward Deployed Engineer role centers on embedded customer delivery — discovery, prototyping, integration, and production rollout. Key signals from the listing: Kubernetes / containers, Python, 5+ years experience, Senior scope.
About Snowflake
Snowflake field engineers drive warehouse migrations and analytics modernization with enterprise buyers. The role is anchored in US-NY-New York, so expect on-site customer work in that region.
Signals in the listing
Stand out for Senior Security Architect, Applied Field Engineering (AFE)
- Lead your application with one paragraph tying Senior Security Architect, Applied Field Engineering (AFE) to a specific customer or deployment you owned — Snowflake hires for shipped outcomes, not tool lists.
- Prepare a 5-minute “week one on site” plan: who you would meet, what you would inspect in their stack, and what artifact you would deliver by day five.
- Show you can go from discovery notes → working integration → production checklist without needing a large internal team.
- State clearance status clearly up front (active, expired, or eligible) and mention any prior NIPR/SIPR, IL5, or government cloud accreditation work — recruiters filter on this early.
- For Kubernetes-heavy roles, describe a cluster you operated: upgrades, networking, secrets, observability, and how you debugged a production outage.
- This role is tied to US-NY-New York — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at Snowflake
- Demonstrate SQL/ELT patterns with a concrete example — Snowflake will probe for specifics, not buzzwords.
- Demonstrate cost governance with a concrete example — Snowflake will probe for specifics, not buzzwords.
- Proof of running a successful migration or cost-optimization project beats generic cloud buzzwords.
- Read recent engineering blog posts, product launches, and customer stories on snowflake.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Overview
Enterprises are modernizing data platforms at an exponential rate to meet demands for innovation, specifically with the rise of Generative and Agentic AI. As the leading AI and BI platform, Snowflake requires a secure-by-design foundation to drive business value. The Security Applied Field Engineering (AFE) organization is at the forefront of this effort, ensuring that security is a strategic accelerator rather than a bottleneck. 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. You will transition customers from legacy, siloed security tools to a unified Security Data Architecture. You will partner closely with Sales, GTM, Engineering, and Marketing to help customers transform their business within the Snowflake AI Data Cloud while maintaining a world-class security posture.
Key
Responsibilities
Field Engineering & Security Architecture
- Security Architecture Foundation: Drive strategic engagements focused on the Security Architecture, ensuring robust foundations across Identity, Data, and Infrastructure for applications built on Snowflake.
- AI Security & Trust Foundations: 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.
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
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com http://careers.snowflake.com