Full-Time

Member of Technical Staff

Security

Prime Intellect

Prime Intellect

11-50 employees

Decentralized GPU compute marketplace for AI

Compensation Overview

$180k - $350k/yr

+ Equity Incentives

H1B Sponsorship Available

San Francisco, CA, USA

Hybrid

Flexible work arrangement: candidates may work remotely or from our San Francisco office.

Category
Software Engineering (2)
,
Required Skills
Service Mesh
Kubernetes
Rust
Python
Vulnerability Analysis
SOC 2
Cryptography
penetration testing
Google Cloud Platform
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
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
Desired Qualifications
  • 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

Prime Intellect builds a decentralized, peer-to-peer platform for AI development. It operates Prime Intellect Compute, a GPU marketplace that aggregates resources from multiple cloud providers so users can access affordable compute time for AI projects. The Prime Intellect Protocol governs open-source AI with community ownership and governance, enabling anyone to contribute compute, capital, and code for distributed model training. Its goal is to democratize AI development by providing a scalable, marketplace-driven, globally distributed environment for training and deploying advanced models.

Company Size

11-50

Company Stage

Early VC

Total Funding

$20.5M

Headquarters

Dover, Delaware

Founded

2024

Simplify Jobs

Simplify's Take

What believers are saying

  • Prime Compute aggregates 12 providers, offering H100s at $1.5-4/hr instantly.
  • Raised $15M to scale open superintelligence stack for agentic AI.
  • BrowserEnv partnership trains browser agents on real websites reproducibly.

What critics are saying

  • Browserbase failure disrupts BrowserEnv pipeline within 12 months.
  • INTELLECT-2 coordination fails, yielding unusable 32B models by Q4 2026.
  • $15M runway exhausts by Q4 2027 without breakeven transactions.

What makes Prime Intellect unique

  • Prime Intellect Protocol enables peer-to-peer GPU marketplace with TOPLOC verification.
  • INTELLECT-2 launches first 32B-parameter globally decentralized RL training run.
  • Environments Hub hosts hundreds of open-source RL environments for agentic models.

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Your Connections

People at Prime Intellect who can refer or advise you

Benefits

Company Equity

Flexible Work Hours

Remote Work Options

Relocation Assistance

Professional Development Budget

Conference Attendance Budget

Growth & Insights and Company News

Headcount

6 month growth

-5%

1 year growth

-7%

2 year growth

24%
Browserbase
Mar 25th, 2026
Introducing browserenv: train browser agents on real websites.

Introducing browserenv: train browser agents on real websites. Harsehaj Dhami Growth Engineer Kyle Jeong Growth Engineer March 25, 2026 TL;DR: Browserbase and Prime Intellect have partnered to launch BrowserEnv, a reinforcement learning environment for training and evaluating browser agents on real web tasks. Everyone wants AI models that can actually use the browser to get work done, but most models weren't trained to interact with real websites. They were trained on static datasets instead of environments where they can practice navigating pages, clicking elements, and completing multi-step workflows. This is why many browser agents look impressive in demos but struggle in real-world use. The missing piece is a reliable and scalable training environment. Training browser agents requires significant infrastructure when running browsers at scale, interacting with live websites without getting blocked, resetting sessions between tasks, and verifying results. This is the infrastructure frontier labs are already building. For example, Microsoft trained and evaluated their computer-use model Fara-7B using Browserbase, which required reliable access to real websites and scalable browser environments for evaluation and reinforcement learning workflows. Browserbase, Inc. has partnered with Prime Intellect to make this infrastructure accessible to everyone with BrowserEnv. BrowserEnv is a reinforcement learning environment designed specifically for training browser agents. It runs on Browserbase, which provides scalable browser infrastructure and access to real websites. Prime Intellect provides the training platform. Together, they make it possible to train and evaluate computer-use models on real browser tasks without building the infrastructure yourself. All you need is a dataset of tasks. Researchers and developers can train open models like Qwen or other computer-use models using reinforcement learning, while BrowserEnv handles browser orchestration, task execution, and verification. Training Qwen 3 VL on WebVoyager with BrowserEnv. To validate its stack end to end, Browserbase, Inc. fine-tuned Qwen/Qwen3-VL-8B-Instruct on real WebVoyager tasks using BrowserEnv and Prime Intellect. Browserbase, Inc. plugged the prime/webvoyager-no-anti-bot environment into Prime's RL pipeline, so the model could practice real navigation flows across sites like Amazon, Allrecipes, GitHub, Booking, and more without getting stuck on anti bot walls. BrowserEnv handled browser orchestration on Browserbase, Prime handled rollouts and optimization, and WebVoyager provided a standardized benchmark of 600 filtered tasks. Browserbase, Inc. started from the public WebVoyager environment in the Prime hub, switched it to CUA mode, and pointed it at Qwen3-VL-8B-Instruct. The training run used a relatively small but realistic configuration: 200 steps, batch size 32, 8 rollouts per example, learning rate 1e-4, and an oversampling factor of 2, with modest parallelism. model = "Qwen/Qwen3-VL-8B-Instruct" max_steps = 200 batch_size = 32 rollouts_per_example = 8 learning_rate = 0.0001 oversampling_factor = 2 max_async_level = 2 [sampling] max_tokens = 512 [[env]] id = "prime/webvoyager-no-anti-bot" args = {mode = "cua", viewport_width = 800, viewport_height = 600, keep_recent_screenshots = 2} In this setup, each training step created or reused a Browserbase session, loaded a WebVoyager task, and let Qwen3-VL act through coordinate based CUA primitives while a verifier judged task completion and produced reward signals. Over the course of the run, the model improved on multi step tasks such as searching, filtering, and extracting information from live pages, rather than just static HTML. The output of this training run is a LoRA adapter that can be easily deployed to run on the Prime Intellect platform. This training workflow is reproducible by anyone with access to a Browserbase and Prime Intellect account. You can even start from the same ingredients Browserbase, Inc. used: BrowserEnv on Browserbase, the WebVoyager no anti bot environment in Prime, and an open vision language model like Qwen3-VL. Frontier labs are already training browser agents this way, and now anyone with access to the internet can do the same. BrowserEnv is generally available today, learn more at browserenv.com and start training your own browser agents. Train your own custom modelLearn more

Bankless
May 1st, 2025
AI ROLLUP: The AI Experiment That's Been Secretly Manipulating You

Prime Intellect just launched INTELLECT-2, the first globally distributed reinforcement-learning run of a 32-billion-parameter model, with experts predicting community-trained systems in the 70-100 B range by year-end - a potential counterweight to hyperscaler dominance.

Prime Intellect
Mar 4th, 2025
15M to Build a Peer-to-Peer AI Protocol

Prime Intellect is building a peer-to-peer protocol for compute and intelligence, enabling collective creation, ownership, and access to sovereign open-source AI. We’re moving beyond centralized AI to empower anyone—from solo GPU operators to global datacenters—to contribute compute, code, or capital and shape the open and decentralized AI ecosystem.

CO/AI
Oct 12th, 2024
Prime Intellect launches initiative to train open model with decentralized computing

Prime Intellect launches initiative to train open model with decentralized computing.

PR Newswire
Jul 25th, 2024
Coinfund Expands Best-In-Class Team, Launches Podcast As Firm Commemorates Nine Years Of Service

NEW YORK, July 25, 2024 /PRNewswire/ -- CoinFund , one of the world's longest-operating cryptonative investment firms and a registered investment adviser, commemorates the firm's 9th anniversary with the announcement of four strategic hires and the launch of a new podcast , Mined with CoinFund.EXPANDING THE TEAMCoinFund proudly announces the addition of four subject matter specialists to support an uptick in deal operations and the long-term growth of the brand.With the addition of New York City-based Adriana Armstrong as Executive Assistant, the firm broadens its leadership support and employee and workplace experiences. Adriana brings over 10 years of internal operations, office management, and executive support to CoinFund, most recently working as a consultant at Illuminate Ventures and New System Ventures.In an effort to further strengthen its operational foundation, CoinFund has bolstered its Finance team with the addition of New Jersey-based Matt Manley as a Finance Operations Associate. Prior to CoinFund, Manley was a Senior Accountant in Withum's Emerging Technology group serving on the Digital Assets and Blockchain team, and brings more than seven years of combined audit and digital asset experience to the role from best in class providers like Copper.co and KPMG.CoinFund announces that Malaysia-based Walter Teng has joined CoinFund as an Investor on the Liquid Investments team, deepening the firm's connectivity in Asia. Prior to CoinFund, Teng served as a liquid investor at MSA Novo, and spent more than two years at FundStrat, most recently acting as Vice President of Digital Asset Strategy where he focused on DeFi and small cap strategies.The firm has also continued to expand its commitment to post-investment services, growing its Marketing team with the addition of New York City-based Cam Thompson. In her newly created role as Content Manager for CoinFund, Thompson will amplify the firm's storytelling via written and visual content. Most recently she served as a Copywriter and Creator Liaison at Celo Foundation and covered the trends of the crypto industry as a web3 beat reporter for CoinDesk."CoinFund is a state of the art investment firm designed for the next generation of the internet built on decentralization technology and web3," commented Jake Brukhman, Founder, CoinFund