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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:

As a Senior Product Manager at Nightfall you'll lead the development and evolution of our latest Data Exfiltration Prevention (Endpoint DLP) product with coverage across SaaS, AI apps, endpoints on macOS, Windows and all major browser platforms. You'll develop a deep understanding of how organizations secure data and identify critical gaps in their data loss prevention approach especially with the evolving usage of AI apps.

Key Responsibilities

• Ship endpoint DLP features fast - building MVPs, gathering feedback, and iterating based on real-world usage

• Define success metrics: agent deployment rates, detection accuracy, remediation rates, exfiltration prevention metrics, system performance to avoid user friction and more

• Work directly with engineering on sprint planning, backlog prioritization to achieve predictable release timelines

• Build competitive differentiation by understanding what competitive vendors do poorly or have lack of coverage with endpoints, AI apps and agentic workflows

• Document technical capabilities clearly for sales engineering, support, and customers - from architecture diagrams to deployment guides

• Work with Sales Engineering and Customer Success during proof of value, customer deployments to ensure successful evaluation and adoption

• Be comfortable presenting the product capabilities and differentiators to CISOs, SecOps teams across customer segments

What you need

Customer-Facing and Collaborative

• 4 to 6 years of product management experience at a SaaS startup with a highly technical product.

• Comfortable joining customer calls, demos, and technical discussions - you can speak credibly about how the product works, handle deployment issues, or

• Experience working closely with sales engineering and customer success - you understand their workflows and help them win deals and secure renewals

• Strong communication skills and an ability to translate technical requirements from security teams into clear product specifications

Execution-Oriented and Scrappy

• Bias for action - you ship fast, iterate based on feedback, and don't wait for perfection

• Comfortable with ambiguity and rapid change - you're building a category-defining product in a startup environment

• Strong prioritization skills - you know what moves the needle vs what can wait

• Entrepreneurial mindset - you'll do whatever it takes to make customers successful, from troubleshooting agent issues to writing KB articles

• Hard-working and resilient - this is a high-intensity role that requires deep focus and relentless execution

Bonus Points

• Prior experience as a founder, security engineer or product manager on an endpoint product or similar hands-on security role

• Understanding of MDM platforms, strong grasp of endpoint DLP and browser extension architecture, security frameworks and limitations across macOS, Windows

• Knowledge of compliance frameworks, AI apps and agentic workflows and how they drive DLP requirements

• Experience with ML/AI-based detection and classification systems

• Background in SaaS security products and understanding of cloud-to-endpoint integration patterns

• Graduated with a Computer Science (or similar) degree