Abhay builds security infrastructure for a world that’s moving faster than legacy tools can keep up with. His work focuses on the intersection of artificial intelligence, offensive security, and cloud-native systems where traditional approaches break down and new design patterns are urgently needed.

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With over a decade of hands-on experience across red teaming, detection engineering, threat modeling, and applied ML, Abhay has helped startups and large-scale engineering organizations navigate complex security challenges, from securing LLM pipelines to designing developer-first security controls.

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He’s worked across the offensive and defensive spectrum: leading adversary simulation efforts, designing threat detection pipelines, and scaling security programs in fast-moving product environments. He’s also built production-grade infrastructure and contributed to open-source projects in the AI and security space.

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Abhay’s current focus is on building AI-native infrastructure that allows teams to adopt machine learning systems without compromising safety, observability, or control. This includes:

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• Securing LLMs and generative AI integrations
• Designing threat models for autonomous and ML-driven systems
• Building developer-facing security primitives that are easy to adopt and hard to misuse
• Helping teams understand how traditional security abstractions break in AI-heavy environments

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He writes and speaks regularly on emerging threats in AI, the operational realities of deploying secure ML systems, and how security teams can evolve their tooling and mindset to keep up with autonomous software.

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Abhay believes the next decade of security will depend on how well we adapt our infrastructure, not just our policies. His work is deeply technical, engineering-first, and grounded in the realities of how systems actually behave in production.