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Member of Technical Staff - Security

Prime Intellect· Engineering
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San Francisco$180k - $350kFull-timePosted 6mo ago

About the role

Security-focused senior engineer building the security posture for Prime Intellect's frontier AI platform, with ownership from threat modeling to incident response and compliance.

Responsibilities

  • Own threat modeling across our entire surface area: multi-tenant training infrastructure, sandboxed execution environments, API surfaces, and internal tooling
  • Design and implement zero-trust networking, identity, and access control across distributed GPU clusters and cloud infrastructure
  • Build secure-by-default patterns for our platform engineers — auth, secrets management, supply chain integrity, container hardening
  • Architect tenant isolation and data boundary enforcement for hosted RL training workloads (customers run arbitrary code in our environments)
  • Develop security frameworks specific to AI infrastructure: model weight protection, training data isolation, checkpoint integrity, gradient privacy
  • Secure the RL training loop end-to-end — from environment execution in sandboxes to reward signal verification and model artifact storage
  • Build detection and prevention for AI-specific attack vectors: prompt injection across agentic pipelines, model exfiltration, adversarial environment manipulation
  • Scope, manage, and run point on external penetration tests across our platform, hosted training infrastructure, and liquid compute layer
  • Build and maintain an internal red-teaming practice — automated and manual — targeting our most critical systems
  • Drive vulnerability management: triage, remediation SLAs, and root cause analysis
  • Build security monitoring and alerting across infrastructure (distributed clusters, Kubernetes, cloud) and application layers
  • Implement runtime security for containerized training workloads and sandboxed environments
  • Own incident response — build the playbooks, run the drills, lead the post-mortems
  • Design audit logging and forensic capability across all customer-facing systems
  • Drive SOC 2 Type II readiness and other compliance frameworks required by enterprise customers
  • Own the security narrative for customer-facing materials — questionnaires, architecture reviews, trust documentation
  • Partner with GTM to unblock enterprise deals that depend on security posture

Qualifications

  • > 5 years in security engineering, infrastructure security, or offensive security roles — ideally at companies operating multi-tenant cloud or compute infrastructure
  • Deep experience with cloud security (GCP preferred), Kubernetes security, and container runtime hardening
  • Hands-on ability to read, write, and audit code in Python and Rust (or strong systems-level language)
  • Experience with network security in distributed systems — service mesh, mTLS, network segmentation across heterogeneous hardware
  • Proven track record managing external penetration tests and translating findings into engineering action
  • Strong fundamentals in cryptography, identity/access management, and secure software development lifecycle

Skills

Required:Threat modelingZero-trust networkingIdentity and access managementContainer securityAI securityPythonRust

Benefits

  • Cash Compensation Range of $180-350k+ with significant equity incentives
  • Based in our San Francisco office
  • Full visa sponsorship and relocation support
  • Professional development budget for courses and conferences
  • Regular team off-sites and conference attendance
  • Opportunity to shape the future of decentralized AI development
Last updated Oct 21, 2026. Interested? Apply on the company site.

About Prime Intellect

Commoditizing Compute & Intelligence

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

AI developmentbessemer-ai-infrastructure-2026compute resourcesdistributed trainingmodelsreinforcement-learning-platformsscience
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