Why This Job is Featured on The SaaS Jobs
Security has become a defining differentiator for cloud data platforms, especially as enterprises bring generative and agentic AI workloads closer to governed data. This Senior Security Architect role sits at that intersection, operating in a field engineering context where architecture decisions are shaped by real customer environments. Within the SaaS ecosystem, it reflects how platform companies are increasingly packaging security as prescriptive reference designs and repeatable patterns, not just controls and checklists.
For a long-term SaaS career, the role offers a vantage point across multiple implementations and maturity levels, from legacy tool consolidation to modern security data architectures and observability. That kind of cross-customer exposure tends to build durable judgment about what scales in multi-tenant, cloud-native platforms, including identity boundaries, data governance, and resilience. The remit also signals opportunities to translate field learnings into internal frameworks and product feedback, a common pathway toward principal security architecture or platform security leadership in SaaS.
This position is best suited to practitioners who enjoy customer-facing technical depth and can move between whiteboard strategy and hands-on guidance. It will fit someone motivated by ambiguity in emerging AI security and governance, and who prefers influencing outcomes through standards, reference architectures, and stakeholder alignment across GTM and engineering teams.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job 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
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
