Product Manager, AI Enablement

Pindrop is the Real Human + Right Human® Identity Trust Platform for the AI era. As AI-driven fraud and deepfakes erode trust in digital communication, Pindrop delivers continuous identity verification and deepfake detection across voice, video, and digital interactions in real time.

Enterprises rely on Pindrop to secure billions of high-risk customer interactions each year, including top U.S. banks, as well as leading insurers and healthcare providers. Powered by models trained on more than 1.5 billion real-world interactions annually and protected by 300+ patents, Pindrop restores trust while reducing fraud, lowering operational costs, and improving customer experience.

Recognized by TIME as one of the Top 10 Most Influential Software Companies of 2026 and by Inc. for Best in Business for Innovation, Pindrop is backed by leading investors including Andreessen Horowitz, IVP, and Capital

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Pindrop is an AI-native company - but outside of Product, Engineering, and Research, most teams are still figuring out how to use AI in ways that actually stick. This role fixes that.

As Product Manager, AI Enablement, you will own the product experience that turns Pindrop's AI capabilities into practical, repeatable workflows across Finance, Rev Ops, People, Recruiting, Customer Success, Marketing, and Legal. You are not an AI trainer or a help desk. You are a product manager whose users happen to be internal - and your job is to map their processes, identify the highest-value problems, build or configure the right agentic solutions, and prove the ROI.

You'll sit within the centralized AI Operations group and work alongside an existing AI practitioner already embedded in Product. The first 50% of your time will focus on Finance and Rev Ops; the rest goes where the highest-value problems are.

• Map processes before touching AI. Sit with stakeholders, document current-state workflows end to end, extract the context and tools involved, and identify precisely where AI can reduce friction - not the other way around.
• Build and manage a portfolio of internal AI tools, agentic workflows, and prompt-based copilots that solve discrete, measurable problems - and push every project past prototype into production.
• Audit AI capabilities already built into tools Pindrop has purchased (e.g., Greenhouse, ERP) before standing up new solutions; use what we've paid for first.
• Extend Pindrop's shared AI platform and agent infrastructure to new use cases rather than creating parallel stacks.
• Design and implement the operating process that moves AI concepts from prototype to production, including evaluation, human-in-the-loop review, rollout criteria, and post-launch monitoring.
• Consolidate learnings across functions - what worked in Finance should be usable in People; what worked in People should be accessible to CS - and build the tooling and documentation that makes reuse real.
• Make the ROI case. Define success metrics, instrument usage, track adoption, and be able to explain clearly what the company is getting for its AI investment.
• Drive adoption through practical enablement - workshops, onboarding paths, office hours, and coaching - focused on giving teams the guardrails they need to use AI well, not just permissively.

• A builder, not just a user. You've gone past prompting and into building - you have a Git Hub (or equivalent) with projects that prove it. You've shipped agentic systems that solve real problems, and you know how different it feels when the last 20% actually works.
• A process mapper first. Before you touch a tool, you understand the workflow. You can sit with a stakeholder, draw out what actually happens today, and find the leverage point - because you know you…