DevSecOps Engineer

Pathos • New York, NY

60d • $180,000 - $200,000 • Hybrid

About The Position

We handle some of the most sensitive data around: patient outcomes, clinical trial records, and the multimodal datasets behind our foundation model, all inside a company that runs on agents with broad, standing access to internal systems. That combination raises the stakes on security in a way most companies never have to think about.
The threat landscape is moving fast too. Capable AI models have lowered the skill floor for finding and exploiting vulnerabilities, so the volume and sophistication of attacks aimed at companies like ours keeps climbing. We need someone who takes that seriously, builds for it before it's a problem, and doesn't treat security as something you check off at the end of a project.
We're hiring a DevSecOps engineer to own security architecture and practice across our AI and data infrastructure: the pipelines, agent tooling, and internal systems that power our BD, clinical development, computational biology, and lab teams. This isn't a compliance-only role. You'll design the guardrails, then get in the code and build them yourself.

Requirements

• Roughly 6+ years in security engineering, DevSecOps, or something close, with real ownership of production security architecture.
• Fluent in Python and/or TypeScript. You can read and write production code, not just configure tools.
• Deep experience with cloud security (GCP preferred, AWS or Azure fine too), IAM design, network security, and secrets management.
• Hands-on experience securing CI/CD pipelines and infrastructure-as-code (Terraform or similar).
• Practical experience building or operating detection and incident response systems, not just reading dashboards someone else set up.
• Comfortable working as an individual contributor with engineers. Once the security foundation is solid, you'll spend real time as a working engineer on the broader platform.

Nice To Haves

• Experience securing agentic AI systems, LLM-powered applications, or MCP-style tooling, including prompt injection defense and agent permissioning.
• Experience in regulated environments handling patient or clinical trial data (HIPAA, GxP, or similar).
• Certifications like OSCP, CISSP, or GCP/AWS security certs are a nice signal but not a requirement.

Responsibilities

• Threat models and security architecture for a system built around large numbers of autonomous AI agents with access to internal tools, data, and MCP-style servers.
• Guardrails, sandboxing, and permissioning for how agents talk to systems and each other, so they can act without excessive standing privileges.
• Secure CI/CD pipelines, infrastructure-as-code review, and automated security testing (SAST/DAST, dependency and secret scanning) built into how we ship, not added on after.
• Monitoring, detection, and incident response tooling tuned for AI-native infrastructure, including anomalous agent behavior, prompt injection attempts, and data exfiltration paths.
• Data governance and access controls for a governed warehouse and knowledge graph holding patient-level and clinical trial data, aligned with HIPAA and relevant regulatory frameworks.
• Cloud security posture across our GCP environment: IAM, network segmentation, encryption, audit logging.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed