Applied AI Engineer (Member of Technical Staff)
Cogent SecuritySan Francisco, CA$100k – $300kPosted 19 March 2026
Job Description
Applied AI Engineer (Member of Technical Staff)
ABOUT COGENT SECURITY
Cogent is an Applied AI Lab building the next generation of AI agents for cybersecurity. AI has fundamentally changed how attacks happen, allowing malicious actors to operate at unprecedented speed and scale. Cogent’s "AI Taskforce" assesses petabytes of enterprise data to remediate these issues before critical breaches occur.
To stay at the cutting edge, we blend frontier research with real-world execution. Alongside our core product work, Cogent Research serves as our applied AI lab, providing the research horsepower needed to make truly agentic security workflows a reality.
Since coming out of stealth, Cogent has experienced rapid growth. We partner with Fortune 500 companies to secure some of the most complex production environments in the world.
We’re backed by Greylock and we’ve built a team with the best minds in applied AI. Our team is comprised of people from:
- Top universities like Stanford, Berkeley, Penn, Duke, Carnegie Mellon, Waterloo
- Unicorn, high-growth companies like Scale AI, Databricks, Stripe, Tesla, Coinbase
- World class cybersecurity experts from Wiz, Abnormal AI, Zscaler
- Preeminent research labs like Deepmind and SAIL
ABOUT THE ROLE
As we onboard our first design partners, Cogent is launching the world's first AI cyber taskforce, which is composed of AI agents capable of human-caliber reasoning for cybersecurity tasks. We are looking for talented, ambitious AI/ML Engineers who are excited to build in the Applied AI space.
WHAT YOU’LL DO & ACHIEVE
- Architect and launch the world’s first AI Cyber Taskforce
- Work closely with our design customers to design and launch our flagship AI agents that are capable of automating tasks in vulnerability management
- Understand business goals, product and technology strategies, and customer requirements and implement business-critical AI systems to achieve them
- Identify appropriate datasets and data representations to support system development
- Decompose existing enterprise security workflows into sub-tasks that can be modeled as an autonomous system
- Experiment with the latest advancements in long-term reasoning and planning to design systems that allows Cogent to evolve the data flywheel of our AI products from initially highly supervised to eventually autonomous and managed by exception
- Build and extend Cogent’s Gen AI Platform
- Implement reusable system components for ranking, retrieval and search systems powered by LLMs for agentic automation
- Put in place frameworks to train, evaluate, and stress-test ML systems, and extend improvements on Cogent’s Gen AI platform
- Stay on top of and when appropriate, propose incorporating cutting edge developments in ML and Gen AI into Cogent’s AI systems
- Help create a robust engineering culture at Cogent
- Onboard, support and uplevel future team members
- Mentor and grow future junior team members
- Actively contribute to Engineering Excellence, Operational Excellence and Recruiting initiatives
WHAT YOU’LL BRING
- Multiple years of relevant experience in developing and deploying AI-driven systems, with a proven track record of architecting practical, production-grade solutions that solve real-world problems
- Expertise in machine learning, deep learning, and AI models, with a deep understanding of how to apply these technologies to build scalable, performant systems in production environments
- Experience with designing and deploying agentic systems and autonomous agents, as well as integrating these AI components into larger applications or products
- Ability to address and navigate real-world scale and performance challenges, ensuring that 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 ... (truncated, view full listing at source)
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