Senior Manager, AI Engineering

Hacker One is a global leader in Continuous Threat Exposure Management (CTEM). The Hacker One Platform unites agentic AI solutions with the ingenuity of the world's largest community of security researchers to continuously discover, validate, prioritize, and remediate exposures across code, cloud, and AI systems. Through solutions like bug bounty, vulnerability disclosure, agentic pentesting, AI red teaming, and code security, Hacker One delivers measurable, continuous reduction of cyber risk for enterprises.

Industry leaders, including Anthropic, , General Motors, Goldman Sachs, Lufthansa, Uber, UK Ministry of Defence, and the U.S. Department of Defense, trust Hacker One to safeguard their digital ecosystems. Hacker One was recognized in Gartner's Emerging Tech Impact Radar: AI Cybersecurity Ecosystem report for its leadership in AI Security Testing and has been named a Most Loved Workplace for Young Professionals (2024).

Hacker One is at a pivotal inflection point in the security industry. Offensive security is no longer optional - it is the standard for forward-thinking companies that want to build trust and resilience in a world where AI-driven innovation and adversaries are moving faster than ever. With the industry shifting, Hacker One stands apart: we combine the ingenuity of the largest security research community with a best-in-class AI-powered platform, trusted by the world's top organizations.

Hacker One is dedicated to fostering a strong and inclusive culture. Hacker One is Customer Obsessed and prioritizes customer outcomes in our decisions and actions. We Default to Disclosure by operating with transparency and integrity, ensuring trust and accountability. Employees, researchers, customers, and partners Win Together by fostering empowerment, inclusion, respect, and accountability.

Remote Locations:
Austin, TX; or Washington, DC

Hacker One is redefining how the world's leading organizations manage cyber risk - and AI is at the center of that transformation. As Senior Manager, AI Engineering, you will own two of the most strategically important product surfaces in our platform:

• AI-Native Intelligence Dashboard - Transform our executive and analytical dashboard into an AI-first experience that helps customers derive maximum value from their Hacker One engagement. Think proactive risk insights, natural language querying, automated remediation prioritization, and measurable reduction in Mean Time to Remediate (MTTR).
• Payments & Monetization - Lead the team responsible for researcher payments and consumption-based billing, ensuring security researchers are paid reliably and Hacker One's contract monetization engine runs cleanly at scale.

You will lead the team of senior engineers, set technical direction, and ship AI-powered capabilities that customers can see, feel, and measure. This is a high-autonomy role with real product ownership and direct customer impact.

Reflecting our Flexible Work philosophy, this is a remote role targeted for candidates within ~50 miles of Washington DC, Boston, or Austin, with in-office presence typically on Thursdays.

At Hacker One, we embrace a Flexible Work approach that gives us the freedom to do our best work while also fostering the connections and community that make us stronger. Reflecting this philosophy, this is a remote role targeted for candidates within ~50 miles of the listed locations above. We believe this balance of proximity and flexibility gives Hackeronies the chance to occasionally come together - fostering collaboration, connection, and in-person moments that enrich our culture - while still preserving the benefits of remote work.

Success in this role will be accomplished by delivering on the responsibilities below in alignment with the Values and Principles that define how we work at Hacker One.

• Multiply Your Impact by leading, mentoring, and developing Engineering Managers and senior engineers, building scalable systems and practices that allow teams to deliver AI-powered solutions consistently and independently
• Own the Outcome for execution across multiple AI engineering teams, ensuring delivery commitments are met, dependencies are actively managed, and teams are accountable for customer-visible impact
• Drive an AI First approach to engineering by embedding AI-powered workflows, agentic systems, and responsible AI practices into how teams design, build, and operate products
• Practice Change Agility by guiding teams through evolving AI technologies, shifting priorities, and emerging security threats while maintaining clarity, momentum, and team health
• Apply First Principles Problem Solving to complex AI and product challenges, breaking problems down to fundamentals and designing durable, scalable solutions rather than short-term workarounds
• Leverage Data-Driven Decision Making to assess system performance, model quality, delivery outcomes, and operational health, using evidence to…