Research and analyze malicious traffic, attacker behavior, and the emerging role of AI in offensive and defensive security
Investigate and document adversarial ML/AI techniques, AI-driven automation, and misuse of generative AI in real-world attacks
Build small tools, LLM-based applications, or datasets that demonstrate AI’s role in security (both protective and adversarial)
Explore and prototype with modern frameworks such as Model Context Protocol (MCP) and agent-based systems
Translate complex findings into articles, reports, visuals, or presentations for a wide range of audiences
Collaborate with a small team of researchers, engineers, and communicators to deliver timely and relevant insights
Represent F5 Labs externally via blog posts, webinars, podcasts, media interviews, and industry events
Support marketing and sales enablement efforts with high-impact research and commentary
Maintain a strong understanding of offensive and defensive practices, with particular focus on web, API, bot, DDoS, and AI-related threats
Optionally, participate in proactive research efforts including honeypots, probing attacker infrastructure, and experimenting with AI-powered defense systems.
Requirements
~10 years of experience in cybersecurity or a closely related field
Strong grasp of common web, cloud, and API protocols and their associated attack surfaces (e.g., HTTP/S, REST, OAuth, DNS, TLS, etc.)
Experience analyzing network, application, or AI telemetry to extract meaningful security insights
Strong coding and data handling skills, especially in Python and Jupyter (SQL or BigQuery a plus)
Ability to prototype with LLM APIs, frameworks, or agents; familiarity with building AI-enabled applications
Excellent written, visual, and verbal communication skills, with a clear ability to tell stories with data
A self-starter who can independently define and deliver meaningful research projects
Public speaking experience or a willingness to represent research externally
Enthusiastic about educating others and promoting good security practices.
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