AI Security Engineer

B2B SAAS data observability software. Join the company that’s building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world’s biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what’s next.

We’re one of the fastest-growing private companies and a leading player in a massive, fast-moving market. With a global workforce, we’re remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.

We are seeking a talented and experienced Staff AI Security Engineer to help build Cribl’s new AI Systems team. In this pivotal role, you will design, implement, and operationalize security and governance frameworks that enable rapid AI adoption to scale safely across Cribl’s internal systems and workflows. This is a foundational role on a newly established team tasked with providing the shared infrastructure, security guardrails, and reusable patterns needed to turn AI from fragmented experimentation into durable company capabilities.

You will be instrumental in bringing security, governance, and safety to Cribl’s rapidly expanding AI footprint, including API tokens, secrets management, MCP security, shadow AI mitigation, AI telemetry, and compliance readiness. The team’s mandate is to provide the “paved road” for AI at Cribl: secure access, governed integrations, reusable workflows, and a platform that enables teams to move faster without creating security, compliance, or operational risk.

This role will be part of the Corporate AI Systems team and will report directly to the Chief Information Security Officer (CISO). It will partner closely with stakeholders across Security, Enterprise Applications, Product, Engineering, IT, Legal, and the various business teams adopting AI to ensure Cribl’s AI capabilities scale securely and pragmatically.

• AI Security Architecture & Governance Define, threat model, and operationalize the security architecture for Cribl’s internal AI platform, including standards, controls, approval patterns, and secure-by-design guidance for AI use cases before they scale into production.
• Shadow AI Discovery & Remediation Partner with Business Operations to maintain visibility into AI tools, licenses, API tokens, MCP servers, and ad hoc workflows in use across the company, and monitor for ungoverned or high‑risk patterns that require remediation.
• MCP Security & Registry Management Own the framework for vetting MCP servers, maintaining an approved registry, defining risk tiers, and enforcing secure connection patterns as MCP adoption expands across teams.
• Secrets, Identity & Token Protection Establish secure patterns for secrets management, non‑human identities, scoped credentials, OAuth-based access, and token governance to enforce least‑privilege access and reduce credential exposure in AI builds.
• Prompt Injection Defense & Safe Execution Controls Design and deploy guardrails for prompt injection defense, deterministic validation, human‑in‑the‑loop approvals, and additional controls for high‑risk workflows that combine sensitive data, untrusted content, and external action.
• AI Telemetry, Detection & Incident Response Partner on building Cribl as the observability backbone for AI systems, including telemetry pipelines, abuse detection, audit trails, threat hunting, and incident…