Product Manager, AI Enablement

Who We Are

Pindrop is a cybersecurity company delivering continuous identity verification across voice, video, and digital interactions. Powered by the Pindrop Intelligence Network, our unified trust platform helps enterprises answer three critical questions:

Is this identity synthetic? Detect AI-generated and manipulated voice and video.
Is this identity risky? Identify fraud, suspicious behavior, and other risk signals.
Is this identity known? Authenticate identities using voice, device, behavioral, and other signals.

Pindrop brings this intelligence together across purpose-built trust engines to help organizations make informed decisions in real time — protecting customers, workforce interactions, and emerging AI-driven interactions.

Pindrop protects billions of high-risk interactions for enterprises, including leading financial institutions, insurers, and healthcare organizations. Its technology is informed by more than 8 billion real-world interactions annually and protected by 300+ patents.

Recognized by TIME as one of the 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 CapitalG.

What you’ll do

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, RevOps, 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 RevOps; the rest goes where the highest-value problems are.

More specifically, you will:

• 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 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.

Who you are

• A builder, not just a user. You've gone past prompting and into building - you have a GitHub (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 can't automate a process you haven't mapped.

• Frontier-fluent and self-directed. You track what's happening at the edge of AI tooling because you're genuinely curious, not because it's required. You know the difference between AI theater and AI value, and you're allergic to the former.

• A translator and teacher. You can walk into a Finance or HR meeting without owning their domain and still build credibility through preparation, curiosity, and practical results. You get energy from turning a skeptic into a confident user.

• Rigorously skeptical. You stress-test outputs, understand where models break down, and hold a high bar before recommending a workflow to a real team. You know what an eval is and why it matters.

Your skill-set

Must-haves:

• Process mapping. You must be able to document a current-state workflow end to end, extract the tools and context involved, and use that map as the foundation for any AI solution.

• 3+ years in product management, product operations, AI enablement, or a closely related role at a technology company with PM-level ownership of scope, requirements, delivery, and metrics.

• Hands-on experience with frontier AI CLIs and coding tools, including Codex, Claude Code, Anti-Gravity, and/or SuperGrok. We will ask to see what you've built.

• Demonstrated ability to build agentic systems that solve a discrete, measurable problem - not a demo, a shipped solution.

• A GitHub profile showing 3-4 built projects is a strong signal; candidates without one will be asked to walk through their work in detail.

• Fluency in context engineering and ontology design; ability to speak to both concepts and apply them in practice.

• Conceptual command of test-driven development and eval-driven development for AI systems; must understand why evals matter and how to define them, even if you're not writing them by hand.

• Proven ability to define success metrics, track adoption, and make the ROI case for AI investments to a skeptical stakeholder.

Nice-to-haves:

• Experience with meta harnesses and multi-agent orchestration frameworks.

• Familiarity with RAG patterns, LLM output evaluation, hallucination mitigation, and release gating in enterprise contexts.

• Exposure to AI acceptable-use policies, data-handling guardrails, or workforce governance frameworks.

• Background in high-growth, AI-native, or B2B SaaS environments where technology is advancing faster than organizational absorption.

• Experience building enablement content, use-case libraries, or office-hours programs from a blank page.

What’s in it for you

Most companies are building AI strategy. Pindrop is past that - we're building AI products for internal users who have real problems and real deadlines, and we need someone who can take that seriously.

This role puts you at the center of a hard and interesting problem: how do you move an organization from scattered AI experimentation to repeatable, measurable AI advantage? You'll have a direct line to the leaders whose teams you're serving, a peer already doing this work in Product, and the mandate to consolidate what's working into something the whole company can use.

Fair warning: the first 60 days will feel exhilarating - every function has problems you can help with. The next 60 will feel hard because shipping the last 20% of an AI solution is where most people stop, and your job is to not stop. If that arc sounds energizing rather than discouraging, you're the right person.

You'll work alongside some of the sharpest technical and creative minds in AI, security, and voice intelligence. We operate with intense focus on execution, and we're a team that genuinely enjoys the work. If you want to build things that matter, teach others to use them, and help shape how a serious AI company operates - this is that opportunity.

Travel: This US-based position, requires at lea