About the role
About Nightfall: Nightfall is the AI-native, unified data loss prevention and insider risk management platform that protects sensitive data across SaaS apps, GenAI tools, email, endpoint devices, and more. Hundreds of customers, spanning AI innovators to top 10 banks, trust Nightfall to detect and stop data exfiltration at scale. Nightfall enables organizations to innovate freely without the risks of losing intellectual property or exposing customer data. Our agentic platform helps security teams regain their time by putting data loss prevention on autopilot. With automatic remediation, security violations can be resolved automatically before they become incidents, and end-users can be automatically trained and coached in the moment to self-heal violations that they introduce. Nightfall is backed by leading VC firms including Bain Capital Ventures (Enrique Salem - former CEO of Symantec), Venrock (early investors in Cloudflare), WestBridge Capital, Pear VC (early investors in Dropbox and Doordash), and a cadre of cybersecurity leaders including Frederic Kerrest (founder of Okta), Maynard Webb (former COO of eBay), Ryan Carlson (President of Chainguard), Kevin Mandia (founder of Mandiant), and many others.
About
the role: At Nightfall AI, we’re building the future of data security with machine learning at its core. Our AI systems detect and prevent data leaks in real time for leading organizations. We’re looking for a motivated, highly talented engineer to join our AI Engineering team. You’ll work with world-class engineers to design and enhance the AI models that power our security products. Learn how to build and scale the underlying system that hosts these models. If you love solving hard problems, experimenting with the NLP model architectures, latest LLMs, eager to dive deep into the internals of the underlying systems, and ultimately make a real impact — this is your chance to jump in early and grow fast. What You’ll Do Build and ship the AI systems that power Nightfall’s Security products. Work hands-on with Python to analyze data, experiment with new natural language or other model architectures, fine tune models, benchmark and monitor model accuracy, build automation for automated training and deployment, real-time inferencing, or designing agentic workflows. Work hands-on with Go to build the microservices that ingest and process data at scale through the use of streaming infrastructure, distributed caching, and highly concurrent execution. Collaborate across engineering and product to turn ideas into live AI features Participate in
