Employee Spotlight: Amit Nene, Engineering Leader

Our team is excited to welcome Amit Nene as Nightfall’s Engineering Leader. Amit brings nearly two decades of experience leading ML innovation, driving platforms at scale, and managing data infrastructures. Read on to learn more about Amit’s notable career, his thoughts on AI, and his vision for Nightfall’s engineering team. 

You’re coming to Nightfall from Uber, Apple, VMware, and more. Tell us about your experience, and how it brought you to Nightfall.

I spent years working at big companies, seeing firsthand how distributed systems work at scale. One of those companies was Uber, where I spent several years working with machine learning (ML) on the fraud detection team as well as on safety teams. That was my origin in ML, and the first time I’d seen ML used to protect sensitive data. 

In line with that experience, I wanted to see AI in action in a new vertical like data leak prevention (DLP). When I first encountered Nightfall, I thought, “Every company needs to have this.” In the past, I often needed to manually address data sharing best practices with engineers, but Nightfall would’ve done that for me with features like its “Human firewall.”

On another note, I was also looking for a company where I could move fast and own a product end to end. Right off the bat, I admired the execution-oriented culture that Nightfall’s Co-Founder and CTO, Rohan Sathe, has built here.

Between the industry-leading product and the results-driven culture, Nightfall seemed like the perfect fit. Now that I’m here, I’m looking forward to making an impact by leading a team that’s at the intersection of security, machine learning, and systems engineering. 

More engineering teams are building and consuming AI than ever before; what are the security risks that these teams need to know about?

First and foremost, engineers can be so focused on the outcomes of their AI models that they might not be aware of the consequences of using sensitive data to train said models. They may accidentally gloss over things like toxic data or privacy violations. If engineers were able to catch these sorts of risks and exposures before AI models hit production, it would go a long way in saving companies from breaches, noncompliance, and other repercussions. Nightfall does just that by helping engineers to build security into their AI apps from the beginning, and scale that security as their models grow. In that way, Nightfall isn’t just AI for security; it’s also security for AI.

What makes you excited about the future of Nightfall? 

Many legacy DLP companies have tacked AI on top of their existing solutions—but Nightfall, on the other hand, was built with AI at the core. With industry-leading AI as a key differentiator, Nightfall has tremendous growth potential. Nightfall’s AI-powered detection has a track record of spotting problems that competitors like Google DLP and Microsoft Purview can’t. 

While Nightfall has made its mark on the cloud security niche, it’s also quickly diversifying its platform to cover a wide range of enterprise security offerings. Looking forward, I’m excited to work at Nightfall as we enhance our AI technology and apply it to new enterprise verticals like email and endpoints.

What advice would you give to engineers who aspire to a similar career path?

Most people who get into the cybersecurity industry are smart and have the drive to learn. But ultimately, to be a leader in the space, you also have to raise the engineering standard of the people around you. My advice? Think beyond the ML and the code you're working on to see how you can produce high impact, influence others, and raise the bar to deliver a truly outstanding product.