Mohamed Alimi is VP of Engineering & Applied Science at Bigeye, where he leads the engineering and applied science for the company’s AI Trust Platform, spanning data observability, lineage, sensitive data scanning, governance, and runtime AI policy enforcement for data rich, highly regulated enterprises.

Before Bigeye, Mohamed built Datadog’s AI Observability product suite, leading a team of 40+ engineers, applied scientists, and managers from concept to launch. He originated the products, secured executive sponsorship, worked directly with customers to shape the roadmap, and drove architecture and design across backend, frontend, and applied science. He also presented LLM Observability in the opening keynote at Datadog DASH 2024.

Earlier, Mohamed held engineering leadership roles at Amazon Alexa AI, where he led teams building large-scale web question answering and streaming systems. At MathWorks, he led teams delivering core Simulink capabilities used by major enterprises to model, simulate, and generate code for complex multidomain systems. During his doctoral studies in theoretical computer science, he worked on probabilistic cellular automata and their connections to fault-tolerant computation and statistical physics, and explored extensions of Kolmogorov complexity in quantum computing. Across these roles, he has combined technical depth, product judgment, and execution discipline to build strong teams and ship complex systems at scale.

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