Director Security Applied Field Engineering

1 week ago


Menlo Park, California, United States Snowflake Full time

Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.

Enterprises are modernizing data platforms at an exponential rate to meet demands for innovation, specifically with the rise of Generative 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 the Director, you will lead a team of elite Security Technical Architects who 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 LEADERSHIP

  • 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: Lead 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): Lead workshops 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 content to accelerate new use case deployments and adoption of native functionality.
  • Voice of the Field: Act as a leadership point of contact and influence product roadmaps by serving as the Voice of the Field to Snowflake's product and engineering teams.

People Leadership & Management

  • Build Elite Teams: Recruit, train, and lead a world-class team of Security AFEs who serve as trusted advisors to CISOs, CTOs, and Lead Security Architects.
  • Player/Coach Mentality: Actively participate in high-stakes engagements, working with your team to build solutions for Zero Trust, complex encryption patterns, and enterprise-grade security data lakes.
  • Skill Cultivation: Develop the team's storytelling, facilitation, and design skills to bring complex customer security journeys to life through human-centric design.
  • Culture of Innovation: Foster a culture of co-creation with customers, encouraging the team to think beyond basic infrastructure into business design outcomes.
  • Operational Excellence: Define and execute against clear KPIs, compensation plans, and execution models to drive consistent field impact and scale across regions.

ON DAY ONE WE WILL EXPECT YOU TO HAVE:

CORE EXPERIENCE & LEADERSHIP

  • 20+ years of industry experience in Data, Security,Networking,Infrastructure or AI Engineering, with 8+ years in a leadership role managing high-performing technical teams.
  • Executive Communication: Exceptional storytelling skills with the ability to deliver compelling presentations to both technical and executive stakeholders.

RELEVANT SECURITY SKILLSETS

  • 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: Deep knowledge of securing cloud and hybrid network architectures, including micro-segmentation, zero-trust principles, and secure deployment of services like Apache NiFi.
  • 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.

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.

The application window is expected to be open until February 6, 2026. This opportunity will remain posted based on business needs, which may be before or after the specified date.

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:

The following represents the expected range of compensation for this role:

  • The estimated base salary range for this role is $252,000 - $330,700.
  • Additionally, this role is eligible to participate in Snowflake's bonus and equity plan.

The successful candidate's starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.

To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form.



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