Gimlet Media

Head of Security and Compliance

San Francisco, CA

Sponsorship not specifiedDetected 51 days ago

AWSAzureCloud PlatformsKubernetesCI/CDMachine LearningCybersecurityIncident ResponseComplianceDNSFirewallZero TrustCommunicationCISSP

About the role

You will have significant ownership over the compliance stack, including policies, controls, evidence collection, audit readiness, vendor risk, and security tooling.
Help define security approaches for AI systems, including model access controls, data protection, third-party AI tooling, auditability, and misuse prevention.
Contribute to broader security and operational readiness efforts including vendor risk management, incident response preparedness, business continuity planning, and security policy development.

This is a highly hands-on role for someone who can design the compliance program, implement the technical controls, and work directly with engineering to make security auditable, scalable, and practical.
Build scalable processes for audit evidence collection, risk tracking, remediation management, and security reporting across technical and non-technical stakeholders.

Working knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
Experience with compliance frameworks such as SOC 2, ISO 27001, NIST, CIS Controls, or CSA CCM.
Familiarity with AI governance frameworks such as NIST AI RMF or ISO/IEC 42001.
Experience with Kubernetes, containers, infrastructure as code, and cloud-native security tooling.

Experience in security risk, compliance, GRC, cloud security, or infrastructure security.
Strong written and verbal communication skills.
Experience implementing or administering GRC platforms, SIEMs, CSPM tools, vulnerability scanners, and ticketing workflows.

Gimlet is building the next generation of AI infrastructure: large-scale AI datacenters and the orchestration platform that coordinates them.
The future of AI will require vastly more compute than exists today. But as AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough. The challenge is making increasingly diverse compute work together.
Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency. Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.
We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale and help define the infrastructure layer for the future of AI.
The future of AI will require vastly more compute than exists today.
But as AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough.
The challenge is making increasingly diverse compute work together.
Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency.
Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.
large-scale AI datacenters and the orchestration platform that coordinates them.

This listing is sourced directly from Gimlet Media's careers page and normalized into a canonical job model.