Product Manager, AI Enablement

Pindrop

5h•$130,000 - $150,000•Remote

About The Position

Pindrop is hiring a Product Manager, AI Enablement to turn the company’s AI capabilities into practical, repeatable workflows for internal teams, including Finance, RevOps, People, Recruiting, Customer Success, Marketing, and Legal. The role sits within the centralized AI Operations group and works alongside an AI practitioner embedded in Product. The initial focus is split evenly: the first 50% of time is dedicated to Finance and RevOps, with the remainder directed toward the highest-value problems across the company. This is an internal product management role focused on mapping business processes, identifying high-value opportunities, and building or configuring AI tools, agentic workflows, and integrations. The role owns solutions from discovery through stable production deployment, including evaluation, human review, rollout criteria, monitoring, adoption, and ROI measurement. It also extends shared AI infrastructure, prioritizes capabilities in tools the company already owns, and makes successful solutions reusable across functions. The successful candidate combines technical building skills with product judgment, process-mapping ability, curiosity about emerging AI tools, and rigor in evaluating model performance. They will help teams adopt AI responsibly through practical enablement such as workshops, onboarding, office hours, and coaching. This is a US-based, remote-first position requiring at least six trips per year for team on-sites, cross-functional workshops, and company events.

Requirements

Ability to document current-state workflows end to end, identify the tools and context involved, and use process maps as the foundation for AI solutions.
At least 3 years of experience 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.
Direct experience scripting (for example, in Python), integrating APIs, and deploying agentic systems that solve discrete, measurable operational problems; experience must include shipped solutions, not only demos.
Hands-on fluency with frontier AI command-line interfaces and coding tools such as Claude Code, Codex, or Cursor.
Fluency in context engineering and ontology design, with the ability to discuss and apply these concepts.
Conceptual command of test-driven development and eval-driven development for AI systems, including why evaluations matter and how to define them.
Ability to define success metrics, track adoption, and make the ROI case for AI investments to skeptical stakeholders.
A GitHub profile or equivalent portfolio with shipped, functional code demonstrating technical building ability; candidates without one may be asked to explain their technical architecture in detail.

Nice To Haves

Experience with meta harnesses and multi-agent orchestration frameworks.
Working knowledge of Python, REST or GraphQL API integrations, and custom tool building using Model Context Protocol (MCP) or similar orchestration layers.
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.
Experience in high-growth, AI-native, or B2B SaaS environments where technology advances faster than organizational absorption.
Experience creating enablement content, use-case libraries, or office-hours programs from scratch.

Responsibilities

Map stakeholders’ current workflows end to end, including the context and tools involved, and identify where AI can reduce friction.
Architect, build, and deploy internal AI tools, agentic workflows, and custom integrations using APIs and automation frameworks, taking projects from prototype to production-ready solutions.
Audit AI capabilities in purchased tools before building new solutions, and make use of existing capabilities where possible.
Extend Pindrop’s shared AI platform and agent infrastructure to support new use cases instead of creating parallel stacks.
Design and implement the operating process for moving AI concepts from prototype to production, including evaluation, human-in-the-loop review, rollout criteria, and post-launch monitoring.
Consolidate learnings across functions and create tooling and documentation that make successful solutions reusable.
Define success metrics, instrument usage, track adoption, and communicate the return on investment for AI initiatives.
Drive practical AI adoption through workshops, onboarding paths, office hours, and coaching, while providing appropriate guardrails.

Benefits

Competitive compensation package, including RSUs for all employees.
Remote-first work environment with flexibility and autonomy.
Regular team on-sites, company-wide events, and intentional in-person gatherings.
Unlimited paid time off.
Health and welfare plans, including an employer-paid employee-only health plan.
Employer contributions to a Health Savings Account.
Vision and dental plans for employees and their families.
Paid parental leave for birth, adoptive, and foster parents.
One year of diaper delivery for a new addition to the family.
Recurring monthly phone and internet allowance.
Enhanced fertility and GLP-1 benefits.
Annual Learning & Development stipend.