Principal Product Manager

HackerRank helps thousands of companies like OpenAI, NVIDIA, and Amazon hire developers based on their skills vs. pedigree, and also nurtures a community of millions of developers to upskill themselves to become next-gen developers. The people at HackerRank care deeply about their work and have an extremely intense work ethic. In many companies, speed & quality is a tradeoff. At HackerRank, it’s not -- we expect you to ship in about half the time that most competent people think is possible while maintaining a standard of quality you’d proudly sign your name on. The only way to make this happen is if you truly love your craft and are deeply committed to growth.

About the role

At HackerRank, trust is everything. The Integrity Platform is at the heart of that promise - ensuring that every assessment result reflects genuine skill and performance. As our Principal Product Manager for Integrity, you’ll be on the team that owns the end-to-end strategy, design, and execution of platform capabilities that safeguard assessment authenticity across the entire HackerRank product suite.

You’ll define and lead the roadmap for a system that supports over 100,000 concurrent user sessions, tackling the evolving challenges of AI-enabled cheating and assessment fraud. This is a mission-critical, high-visibility role with direct exposure to the executive team, including the CEO, and deep cross-functional collaboration with engineering, ML, and customer-facing teams.

What you’ll do

• Lead Cross-Product Integrations – Partner with product leaders across all HackerRank lines to embed integrity solutions seamlessly into every experience.
• Collaborate with ML & Engineering – Work closely with our ML engineering team to design detection systems and models that proactively surface suspicious activity.
• Deliver Scalable Platforms – Drive the roadmap for scalable, resilient systems capable of supporting high-volume concurrent sessions with real-time accuracy.
• Represent the Voice of the Customer – Engage directly with enterprise customers to understand their security concerns and translate them into product opportunities.
• Measure & Improve Impact – Define success metrics, monitor key integrity signals, and continuously iterate on solution effectiveness.
• Lead the end-to-end delivery of AI/ML-powered integrity capabilities, including designing eval frameworks, running annotation exercises for key user flows, and holding a high bar for model quality before and after launch.

Who you are

• 5+ years of product management experience, with strong ownership of complex, technical systems
• Comfortable working deeply with ML and engineering teams
• Has built or owned shared platforms, not just features
• Confident and credible in customer-facing, high-stakes problem spaces
• Demonstrates strong judgment under pressure and takes end-to-end ownership

Even better if you have

• Early-stage startup experience
• Prior engineering background
• Experience in HR tech, especially products used for technical hiring or assessments
• Experience with fraud, abuse, trust, security, or risk systems
• Direct ownership of ML-powered or rules-based detection systems
• Built products used at high scale with real-time or near–real-time constraints
• Experience working with enterprise customers on sensitive or regulated workflows

You will thrive in this role if you

• Own from Concept to Launch: You’re a builder who thrives on seeing an idea through every phase-from vision to customer impact.
• Think Strategically: You can simplify complex systems, anticipate risks, and make tough tradeoffs that optimize for long-term scalability and trust.
• Love High Stakes: You’re energized by ambiguity, urgency, and the need to make thoughtful decisions that have executive visibility and company-wide implications.
• Have a Bias for Action: You favor experimentation and iteration over perfection - learning fast and delivering value faster.
• You are deeply fluent in applied AI and have shipped ML-powered products where you personally drove eval design, data and annotation workflows, and the rigor needed to trust models in real customer-facing systems.
• Communicate with Influence: You can distill technical complexity into clear, compelling narratives for executives, customers, and engineers alike.