Senior Program Manager, AI Ops (GTM)

Role overview

This role leads the internal artificial intelligence program for a large revenue organization, serving as the founding AI Operations product and program manager. The position sits at the intersection of business strategy and engineering, shaping how thousands of sellers and GTM colleagues use generative AI to work more productively. It combines product ownership, agile delivery, vendor evaluation, and policy leadership in a fast-evolving space.

Responsibilities

- Act as the bridge between the revenue organization and a team of internal engineers, translating prioritized use cases into user stories, development requirements, and aligned delivery plans. - Own the internal AI roadmap covering agents, applications, and prompts, running an agile cycle that includes intake, sizing, build, QA, release, and ongoing support. - Establish and maintain organization-wide policies, standards, and processes for responsible AI usage, partnering closely with IT and security leadership. - Collaborate with business and data teams to identify, curate, and govern the data sources that feed internal AI systems. - Model operating costs for AI workloads, including token consumption, model selection, and usage forecasts, and keep spend within ROI targets. - Lead vendor evaluations from initial vetting through procurement, infosec, and legal, including defining trial success criteria and comparing external tools against internal builds. - Brief executive sponsors and business leaders on technical concepts in clear, outcome-focused language.

Requirements

- 5 or more years of product or program management experience, with at least 2 years working directly alongside engineering teams. - 2 or more years of hands-on fluency with generative AI fundamentals, including prompt engineering techniques, retrieval-augmented generation pipelines, and multi-agent orchestration. - Demonstrated ability to model LLM operating costs and tie usage forecasts to business return. - Track record of creating business cases that justify internal tooling investments. - Comfortable running agile delivery for AI work, including backlog triage, sprints, rapid experimentation, and post-release monitoring. - A hybrid background that lets you discuss implementation details with engineers while also navigating nuanced problems with sales and revenue stakeholders.

Benefits and work setup

- Compensation range of roughly $140,000 to $157,000 USD, with consideration for education, experience, and location. - Benefits package includes medical, pharmacy, dental, and vision coverage, paid time off and sick leave, short- and long-term disability, life insurance, and a 401(k) contribution. - Some roles may include restricted stock units, subject to eligibility.