We're seeking a Senior Security Researcher & Team Lead to own and drive security research domain from the ground up. This is a leadership-first role - you'll build and guide a research team, define a new frontier in AI and agentic security, and shape the methodologies and standards that don't yet exist in the industry. If you thrive in ambiguity, love creating structure where there is none, and want to leave a real mark on an emerging security domain, this role is for you.
You'll investigate emerging attack surfaces, architect and implement detection mechanisms, and validate your findings in production environments protecting Fortune 500 customers. It's a high-ownership position that blends deep technical research with strategic thinking and team leadership - with a real sense of urgency to shape the AI security landscape not just, but for the entire security community.
Responsibilities:
Lead and mentor a security research team, driving vulnerability and threat research that generates product value and protects Fortune 500 customers in production environments.
Take end-to-end ownership of detection mechanism design for agentic AI applications - from initial hypothesis through experimentation to production-grade implementation.
Apply expertise across cloud, identity, web, and API security to map and address the evolving AI threat landscape.
Apply LLMs, Agentic AI, and machine learning models to detect security vulnerabilities.
Collaborate closely with engineering and product teams to translate research into actionable, shippable security capabilities.
Requirements: 2+ years of experience in a team leader or tech lead position.
4+ years in security research, with hands-on experience in at least 2 of the following domains: cloud, web, API, identity, or supply chain security - and a solid working familiarity with the rest.
Strong coding and data analytics skills in Python, JavaScript, and Bash, with proficiency in SQL-like queries.
Proven experience building detection mechanisms as part of a security product or detection engineering practice.
Hands-on experience working with AI models in production - including agentic AI systems and LLMs - this is a must.
Experience with the full ML lifecycle, and building machine learning or deep learning models - a significant advantage.
High comfort with ambiguity - ability to define direction and execute without predefined guidelines.
Curiosity, creativity, and a self-driven approach to research and leadership.
sense of urgency in shaping the AI security landscape for the entire security community
This position is open to all candidates.