Member of Technical Staff - Security

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. 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. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own. Role Impact 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. This role owns the security posture of everything we ship: the hosted RL training platform, distributed GPU infrastructure, liquid compute marketplace, and all customer-facing surfaces. 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. 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. Core Technical Responsibilities Preventive Security & Secure Architecture 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) AI-Native Security 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 Offensive Security & External Engagements 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 Detection, Response & Observability 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 Compliance & Customer Trust 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 Technical Requirements 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 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) Experience building security programs from scratch at a high-growth startup SOC 2, ISO 27001, or FedRAMP compliance experience Open-source security tooling contributions Familiarity with eBPF, Falco, or similar runtime security tools What We Offer Cash Compensation Range of $180-350k+ with significant equity incentives Flexible work arrangement (remote or 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 You’ll be the foundational security hire at a company where security is existential — not a checkbox. 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. We value intensity and ownership over credentials. If you’ve built security programs at infrastructure companies, broken into systems professionally, or have deep conviction about how AI infrastructure should be secured — we want to talk. #J-18808-Ljbffr Prime Intellect