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Salary: USD 100,000 - 300,000 / annual
Cogent Security is an Applied AI Lab building the next generation of AI agents for cybersecurity. The company has recently emerged from stealth and is experiencing rapid growth, partnering with Fortune 500 companies to secure complex production environments. Backed by Greylock, Cogent's team includes talent from top universities (Stanford, Berkeley, Penn, Carnegie Mellon), high-growth companies (Scale AI, Databricks, Stripe, Tesla, Coinbase), leading cybersecurity firms (Wiz, Abnormal AI, Zscaler), and preeminent research labs (DeepMind, SAIL).
In this role, you will architect and launch Cogent's flagship AI Cyber Taskforce—a suite of AI agents capable of human-caliber reasoning for cybersecurity tasks. You will work closely with design partners to design and deploy agents that automate vulnerability management workflows. Key responsibilities include understanding business goals and customer requirements, identifying appropriate datasets and data representations, decomposing enterprise security workflows into autonomous sub-tasks, and experimenting with cutting-edge long-term reasoning and planning techniques to evolve Cogent's data flywheel from supervised to autonomous systems.
You will also build and extend Cogent's Gen AI Platform by implementing reusable system components for ranking, retrieval, and search systems powered by LLMs. You'll establish frameworks to train, evaluate, and stress-test ML systems, and stay current with cutting-edge ML and Gen AI developments to incorporate them into Cogent's AI systems.
Beyond individual contribution, you will help create a robust engineering culture by onboarding and upleveling team members, mentoring junior engineers, and actively contributing to engineering excellence, operational excellence, and recruiting initiatives.
REQUIREMENTS:
- Multiple years of relevant experience developing and deploying AI-driven systems with a proven track record of architecting practical, production-grade solutions
- Expertise in machine learning, deep learning, and AI models, with deep understanding of how to apply these technologies to build scalable, performant systems in production
- Experience designing and deploying agentic systems and autonomous agents, and integrating AI components into larger applications or products
- Ability to address real-world scale and performance challenges, ensuring AI models and systems are efficient, robust, and performant under production constraints
- Familiarity with cutting-edge AI technologies including reinforcement learning, natural language processing, computer vision, and large-scale generative models
- Proven ability to work iteratively and collaborate with cross-functional teams to evolve AI models and systems that meet evolving product needs
- Passion for staying at the forefront of AI advancements and continuously learning emerging techniques
