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Snowflake

Security Architect, Applied Field Engineering

Snowflake is hiring a Security Architect, Applied Field Engineering in Menlo Park, United States. It pays $140k-$184k a year and Level rates it ; you can apply on Snowflake.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this cybersecurity role: the daily work is on AI products, without building the model.
  • The posting mentions AI agents among its tools and skills.
  • Level classes it as a senior role.
  • Snowflake has 360 other open roles on Level.
  • Posted in the last few days.

AI in this role

ai-agents

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.

Security Architect, Applied Field Engineering (AFE)

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

How we rate this

Security Architect, Applied Field Engineering at Snowflake rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Also common in cybersecurity jobs at this level

Pay

This job starts at
$140k
Typical cybersecurity job
$159k

This posting starts 12% below the typical cybersecurity job. See cybersecurity jobs

Questions you could be asked

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  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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