Two environments. Two different scales of complexity. One consistent engineering approach. Harsh Singhal's professional arc from consumer platform safety to enterprise AI governance covers more distance than a job title change suggests. The social media platforms he worked on served hundreds of millions of users across dozens of languages and cultural contexts, and the enterprise environments he works in now serve organizations where a single data governance failure can trigger regulatory consequences, legal liability, and reputational damage that no algorithm can undo. What connects both worlds is the same core conviction: safety and governance only work when they are built into the system, not bolted onto it afterward.
Singhal currently works as a Software Engineer at Glean, the enterprise AI company, where his focus is on data security, AI governance, and applying machine learning to the challenge of making enterprise AI trustworthy at scale. Before Glean, he spent more than 18 years across LinkedIn, Netflix, Adobe, and Koo, building production AI systems in environments where getting safety wrong had direct and visible consequences for real users.
