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Staff AI Security Engineer

1 hour, 53 minutes ago
United States
Full-time
Lead
AI (Artificial Intelligence)
Artificial Intelligence and Machine Learning
Confluence JIRA LLM Microservices NetSuite OAuth Salesforce Secrets Management SIEM
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Cribl

Cribl

Cribl provides a unified data management platform specifically designed for IT and security data, enabling users to explore, collect, process, and access their data at scale while offering enhanced control and flexibility in managing their data workflows.

IT Services
251-1K
Founded 2018
$402M raised
View All Jobs 52

Description

  • Define and operationalize security architecture, standards, controls, and approval patterns for Cribl’s internal AI platform.
  • Partner with Business Operations to discover and remediate shadow AI tools, licenses, API tokens, MCP servers, and ad hoc workflows.
  • Own the framework for vetting MCP servers, maintaining an approved registry, and enforcing secure connection patterns.
  • Establish secure patterns for secrets management, non-human identities, scoped credentials, OAuth access, and token governance.
  • Design guardrails for prompt injection defense, human-in-the-loop approvals, and safe execution of high-risk AI workflows.
  • Partner on AI telemetry pipelines, abuse detection, audit trails, threat hunting, and AI-specific incident response.
  • Work with Compliance to prepare documentation and controls for AI governance frameworks and customer requirements.
  • Set security controls and review patterns for AI-assisted internal development, including secure coding and AI-generated code.
  • Define and track AI security metrics such as exposure, control coverage, incident trends, and review turnaround.
  • Collaborate with Security, Enterprise Applications, Product, Engineering, IT, Legal, and business teams to scale AI securely.

Requirements

  • 7+ years of experience in security engineering, application security, cloud security, identity and access management, detection engineering, or a related technical security role.
  • Hands-on experience with modern LLM and agentic systems, including prompt injection, tool use, model access, RAG, AI coding tools, and API-driven integrations.
  • Proven experience with OAuth, service identities, secrets management, RBAC/ABAC, scoped permissions, auditability, and secure-by-default architecture patterns.
  • Experience designing risk-tiered controls, approval models, and guardrails that balance innovation with compliance and operational needs.
  • Ability to operationalize telemetry, define detections, investigate security signals, and build response paths for new threat surfaces.
  • Familiarity with enterprise AI governance and control frameworks such as NIST AI RMF, ISO 42001, SOC 2, GDPR, or SOX.
  • Strong written and verbal communication skills for explaining risk and tradeoffs to engineers, stakeholders, and senior leaders.
  • Comfort building the first version of registries, standards, playbooks, and guardrails in ambiguous environments.
  • Preferred: experience with AI development tools like Claude Code, AWS Bedrock, or similar enterprise AI platforms.
  • Preferred: experience with MCP, API security, gateway technologies, tool-use architectures, multi-agent workflows, SCA/SAST/DAST, SIEM/telemetry pipelines, or secure software delivery controls.

Benefits

  • Salary range of $128,000 to $200,000, depending on geographic location and experience.
  • Health, dental, vision, short-term disability, and life insurance.
  • Paid holidays and paid time off.
  • Fertility treatment benefit.
  • 401(k) retirement plan.
  • Equity compensation.
  • Eligibility for a discretionary company-wide bonus.
  • Remote-first work environment.

Interested in this position?

Apply directly on the company website

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