Benjamin Stevens is a senior cybersecurity consultant, renowned AI and cloud security researcher, and advanced red teamer who blends deep analytical expertise with elite offensive security and cloud engineering capabilities. With a foundation in data science, machine learning, and large-scale analytics, he specializes in securing both modern AI systems and complex multi-cloud infrastructures deployed at enterprise scale.
Benjamin has partnered with FAANG organizations, Fortune 100 companies, U.S. government agencies, and intelligence-adjacent software and hardware providers across the globe to build, assess, and mature their AI and cloud security programs. He is known for taking organizations from having little to no formal security posture in these domains to operating at a highly mature, governed, and defensible state. His work spans secure cloud architecture, AI governance, ML pipeline hardening, and the integration of AI- and cloud-specific controls into enterprise environments.
In addition to strategy and program development, Benjamin delivers deeply technical, actionable offensive insights. His red team and research experience includes adversarial ML, LLM robustness testing, model inversion, cloud attack path simulation, identity and access exploitation, and full-stack penetration testing across AWS, Azure, and hybrid infrastructures. He leverages his analytics background to model attacker behavior and uncover subtle systemic risks, helping organizations understand not only how their AI and cloud systems might be compromised, but what the real-world operational impact would be.
Whether stress-testing generative models, reverse-engineering cloud attack surfaces, architecting secure ML pipelines, or advising executive leadership on emerging threats, Benjamin operates at the critical intersection of machine learning, cloud security, and offensive tradecraft. His mission is to ensure the global adoption of next-generation AI and cloud technologies is supported by resilient, trustworthy, and security-forward foundations—especially within the world’s most sensitive and mission-critical environments.
I build software that makes complex things simple, with an AI-forward focus that never cuts corners on fundamentals. Recent work spans multi-brand authentication for NBCUniversal and a RAG platform at Hearst (modular connectors, OpenAPI, AWS Bedrock).
My bar is high-fidelity engineering: understand the system, choose a design that will age well, making it performant and secure (my background in pentesting helps) and measure what matters. When work crosses teams, I’m good at reducing ambiguity - set a plan people can agree on, instrument it so we can learn, then deliver.
Billiards taught me iteration; life in and around Ukraine taught me urgency. I’m motivated by learning in public with smart people, pushing my own ceiling, and building things that are genuinely useful.
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