Primeintellect

Primeintellect

Member of Technical Staff - Security

San Francisco · Staff+

Sponsorship not specified$180k-$350kDetected 14 days ago
PythonRustDistributed SystemsFull-Stack DevelopmentDatabricksGCPCloud PlatformsKubernetesDatadogMachine LearningCybersecurityNetwork SecurityIncident ResponseComplianceSupply ChainZero TrustResearchLeadership

About the role

  • The next generation of AI companies, enterprises, and research teams do not just need more GPUs.
  • ROLE IMPACT Security is the single highest-stakes function at Prime Intellect.
  • You'll be the first dedicated security hire and will define how we think about security as a company - from threat modeling and secure architecture to incident response and compliance.

Responsibilities

  • the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
  • You'll work directly with engineering, research, and leadership to embed security into every layer of the stack, and you'll manage relationships with external penetration testers and security auditors to continuously validate our defenses.
  • 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
  • Full visa sponsorship and relocation support
  • As we scale to support frontier AI labs and enterprises running their most critical training workloads on our platform, you'll build the security org from the ground up and have direct influence on company strategy.

Requirements

  • 5+ years in security engineering, infrastructure security, or offensive security roles - ideally at companies operating multi-tenant cloud or compute infrastructure

Nice to have

  • Experience securing GPU infrastructure or ML training pipelines
  • Background in offensive security - CTFs, bug bounties, red team engagements
  • Familiarity with AI-specific threat models (model extraction, training data poisoning, sandbox escape)
  • SOC 2, ISO 27001, or FedRAMP compliance experience
  • Open-source security tooling contributions
  • Familiarity with eBPF, Falco, or similar runtime security tools
  • Professional development budget for courses and conferences
  • Regular team off-sites and conference attendance

Skills

  • 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
  • Secure the RL training loop end-to-end - from environment execution in sandboxes to reward signal verification and model artifact storage

Compensation

  • Cash Compensation Range of $180-350k+ with significant equity incentives

Benefits

  • Cash Compensation Range of $180-350k+ with significant equity incentives
  • Flexible work arrangement (remote or San Francisco office)

Company info

  • Security is the single highest-stakes function at Prime Intellect.
  • Our customers - from frontier AI labs to enterprises - trust us with their most valuable assets: proprietary models, training data, and the compute that powers them.
  • Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models.
  • Apply now and join us in our mission to make powerful AI models accessible to everyone.

Visa & Work Authorization

  • Full visa sponsorship and relocation support
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This listing is sourced directly from Primeintellect's careers page and normalized into a canonical job model.