Scale Engineer

Security Architect, Applied Field Engineering

Security Architect · Senior · Full Time

US-CA-Menlo ParkUSD 140k – 184k1d ago
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Role

What you'll do.

This is a Senior Security Architect role at Snowflake's Applied Field Engineering organization, responsible for driving strategic customer engagements and building prescriptive security frameworks for enterprise AI Data Cloud deployments. The role combines field engineering expertise with security architecture leadership, focusing on transitioning enterprises from legacy security tools to unified Security Data Architectures while ensuring secure AI adoption through Snowflake's platform. Requires 5+ years of industry experience in Data, Security, Networking, or AI Engineering with deep expertise in generative AI security, IAM, cloud networking, and enterprise governance frameworks.

Responsibilities

  • Security Architecture Foundation & Strategic Engagements: Drive customer-facing strategic engagements focused on designing robust Security Architectures across Identity, Data, and Infrastructure layers for applications built on Snowflake. Position security as a strategic accelerator while establishing credibility with enterprise architects and senior leadership as a trusted security advisor.
  • AI Security & Secure Agentic AI Framework Architecture: Support customer strategy for secure AI adoption by architecting trusted Agentic AI frameworks where Cortex Agents operate within governed boundaries with autonomous orchestration while inheriting Snowflake's native security perimeter. Leverage Snowflake Cortex to bring state-of-the-art LLMs directly to customer data within secure environments, ensuring proper governance and compliance.
  • AI Governance, Content Filtering & Observability: Deploy Cortex Guard and AI Observability solutions to filter harmful content and provide transparent, explainable AI interactions through rigorous monitoring and tracing. Enforce Role-Based Access Control (RBAC) and data masking across all AI-driven insights and automated actions to maintain security and auditability of agent-driven operations.
  • Modern Security Operations (SecOps) Transformation: Deliver hands-on workshops and technical engagements to transition customers from legacy security infrastructure to advanced SIEM Augmentation, Log Ingestion (OpenTelemetry/Logs into Snowflake), and Cybersecurity Data Lake architectures. Provide prescriptive guidance on modernizing security operations through the Snowflake platform.
  • Identity, Governance & Compliance Framework Development: Build repeatable reference architectures and frameworks for Identity Access Management (IAM), Data Governance, Row-Level Security, Column-Level Encryption, and compliance controls. Create accelerators for well-architected deployments aligned with regulatory frameworks including SOC 2, HIPAA, GDPR, and emerging AI regulations.
  • Business Continuity & Disaster Recovery Architecture: Guide customers through end-to-end Business Continuity/Disaster Recovery (BC/DR) journeys, including multi-region deployment patterns, failover strategies, and measurable recovery time objectives. Establish resilience best practices and compliance patterns for critical data workloads on Snowflake.
  • Technical Content & Tooling Development: Drive creation of relevant technical content, security tooling, and demonstrations showcasing security best practices and accelerating adoption of new platform functionality. Develop technical resources, reference implementations, and security use case libraries that support Sales, GTM, and customer success initiatives.
  • Voice of the Field & Product Influence: Serve as the Voice of the Field to Snowflake's product and engineering teams, translating customer security requirements, pain points, and emerging threats into actionable product feedback and roadmap recommendations. Influence product direction based on field intelligence and enterprise security trends.

Qualifications

What we look for.

Technical

  • Generative AI & LLM Security

    Deep technical understanding of Generative AI security risks including prompt injection, data leakage, model poisoning, and adversarial attacks. Hands-on experience implementing LLM security mitigations and using AI safety frameworks and tools like content filtering systems for production AI deployments.

  • Agentic AI Governance & Autonomy Controls

    Expertise in governing autonomous AI agents with focus on human-in-the-loop controls, explainability, auditability, and decision logging. Understanding of agent orchestration frameworks, autonomous workflow management, and ensuring accountability for agent-driven actions across enterprise systems.

  • Data Privacy & Anonymization Techniques

    Mastery of advanced data privacy techniques including Differential Privacy, tokenization, pseudonymization, data masking, secure multi-party computation, and secure sandboxing. Ability to design privacy-preserving architectures for sensitive training data and inference workloads in AI systems.

  • Identity & Access Management (IAM)

    Expert-level expertise implementing modern authentication and authorization protocols including OAuth 2.0, OpenID Connect, SAML 2.0, and SCIM. Proficiency designing and deploying Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and identity governance across cloud, hybrid, and on-premises environments.

  • Secure Cloud & Hybrid Networking

    Hands-on expertise securing cloud and hybrid network architectures including micro-segmentation, zero-trust principles, network policy enforcement, and secure deployment of data integration services. Experience with secure VPC/VNET design, service-to-service networking, and cloud connectivity patterns.

  • Container & Kubernetes Security

    Proficiency securing the container lifecycle from build time (image scanning, vulnerability management) to runtime (Pod Security Standards, network policies, service mesh). Expertise in Kubernetes security controls, secrets management, RBAC policies, and hardening container deployments at scale.

  • Platform Observability & Security Monitoring

    Proficiency implementing observability for security including centralized logging, comprehensive monitoring, distributed tracing, and security event correlation. Experience with SIEM integration, log aggregation, anomaly detection, and building security data lakes for threat investigation.

  • SQL, Python & API Development

    Hands-on coding expertise with SQL for complex data manipulation and security analytics, Python for security automation and scripting, and REST/GraphQL APIs. Ability to develop security tooling, automated policy enforcement, and analytical queries for security investigations.

  • Governance, Risk & Compliance (GRC)

    Strong background aligning security programs with regulatory frameworks including SOC 2 Type II, HIPAA, HITRUST, GDPR, FedRAMP, and industry-specific standards. Experience designing continuous monitoring programs, audit processes, and compliance automation for regulated enterprises.

Education

  • Bachelor's Degree in Computer Science or Related Field

    Formal education in Computer Science, Information Security, Information Technology, or related discipline. Equivalent professional certifications and extensive hands-on experience can substitute for formal degree requirements.

Experience

  • 5+ Years in Security, Data, or Infrastructure Engineering

    Minimum 5 years of hands-on industry experience in Data Security, Cloud Security, Networking, Infrastructure Security, or AI Engineering roles. Should demonstrate progressive responsibility in designing and implementing security architectures for enterprise environments.

  • Customer-Facing & Enterprise Architecture Experience

    Proven track record acting as a trusted security advisor to enterprise architects, CISOs, and C-level stakeholders. Experience translating complex technical security concepts into business value and establishing credibility with senior leadership across multiple customer engagements.

  • Cloud Platform Security Experience

    Hands-on experience securing cloud and hybrid infrastructure, including cloud-native security controls, identity federation, multi-tenant isolation, and cloud data platform security. Familiarity with major cloud providers (AWS, Azure, GCP) and their security services.

  • Data Platform Security & Governance

    Experience designing and implementing security controls for data warehousing, data lakes, or analytics platforms. Proficiency in implementing data governance, access control policies, encryption strategies, and compliance controls for data-centric architectures.

Skills

Required

  • Generative AI Security Architecture

    Proven ability to design end-to-end security architectures for LLM and AI applications, addressing model security, data protection, and autonomous agent governance at enterprise scale.

  • Enterprise Cloud Security

    Advanced expertise in designing and implementing security solutions across cloud platforms with deep knowledge of cloud-native security controls, identity federation, and cloud data platform security.

  • IAM & Access Control Design

    Expert ability to design modern IAM systems with OAuth 2.0, OpenID Connect, and advanced RBAC/ABAC models that work seamlessly across cloud and on-premises environments for multi-cloud enterprises.

  • Data Governance & Privacy Architecture

    Strong capability designing comprehensive data governance frameworks including classification schemes, access policies, encryption strategies, and privacy-preserving techniques for sensitive and regulated data.

  • Technical Communication & Storytelling

    Excellent ability to distill complex security concepts into compelling narratives for both technical architects and business stakeholders. Proven skill delivering engaging technical demonstrations, whiteboard sessions, and executive presentations.

  • SQL & Security Analytics

    Proficient writing complex SQL queries for security analytics, threat investigation, compliance reporting, and building security data lakes. Ability to translate security requirements into data-driven analytical solutions.

  • Platform Observability & Monitoring

    Strong expertise designing security monitoring and observability solutions including centralized logging, SIEM integration, anomaly detection, and distributed tracing for threat detection and investigation.

  • Zero-Trust & Modern Network Security

    Deep understanding of zero-trust architecture principles with ability to design and implement micro-segmented networks, least-privilege access models, and modern network security controls for cloud environments.

Preferred

  • Snowflake Platform Experience

    Nice to have

    Hands-on experience with Snowflake for security analytics, SIEM augmentation, log ingestion, or building security data lakes. Familiarity with Snowflake's security features, Cortex, and ecosystem accelerates time-to-productivity.

  • Cortex & Advanced AI Security Tools

    Nice to have

    Experience with Snowflake Cortex, Cortex Guard, or similar LLM safety frameworks for content filtering, adversarial testing, and AI safety implementation. Knowledge of AI observability and explainability tooling is advantageous.

  • Python Security Automation

    Nice to have

    Proficiency using Python to develop security tools, automation scripts, and security orchestration solutions. Experience with security frameworks and libraries that streamline security testing and policy enforcement.

  • OpenTelemetry & Advanced Logging

    Nice to have

    Familiarity with OpenTelemetry for distributed tracing and comprehensive logging strategies. Experience implementing OTel-based observability for security use cases and centralized log ingestion architectures.

  • Kubernetes & Container Security at Scale

    Nice to have

    Hands-on experience securing Kubernetes clusters in production environments with expertise in pod security policies, network policies, service mesh security, and secrets management at enterprise scale.

  • CISSP or Advanced Security Certification

    Nice to have

    CISSP (Certified Information Systems Security Professional), CCSK (Certified Cloud Security Knowledge), or equivalent advanced security certification demonstrating depth of security knowledge and professional commitment to the field.

  • AI Regulatory & Compliance Knowledge

    Nice to have

    Understanding of emerging AI regulations such as EU AI Act, AI Bill of Rights, and sector-specific AI compliance requirements. Knowledge of how AI security controls map to regulatory frameworks and compliance requirements.

  • Multi-Region Deployment & DR Patterns

    Nice to have

    Experience designing and implementing Business Continuity/Disaster Recovery solutions with multi-region failover, data replication, and recovery point/time objectives for critical enterprise systems.

Compensation

Pay and benefits.

Base·USD 140,000 – 183,700

Full posting

Original listing.

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

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