Technical Program Manager, Expert Engagement and Voice of Customer (AI)

Meta•Menlo Park, CA

12d•$199,000 - $272,000

About The Position

Meta is building AI agents to take on routine professional work across functions such as Finance, Legal, People, and Sales. The models learn from experienced professionals who opt in to demonstrate their workflows; this work is standardized into workflows, evaluations, and training data to improve Meta’s AI models at professional work. The Technical Program Manager runs the expert engagement program end to end, including identifying experts for priority workflows, onboarding them, capturing their work at high quality, and turning each cycle into results for partner teams. The role also owns the Voice of Customer program, converting feedback from experts and partner teams into product and process improvements. This person serves as the program’s operational engine and primary interface with partner organizations, building a repeatable engagement model that can scale without requiring individual hand-holding.

Requirements

Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
12+ years of experience in technical program management, software engineering, or systems engineering, with demonstrated ownership of portfolio-defining programs across multiple engineering organizations.
Experience delivering technical programs from inception to delivery.
Experience running recurring operational programs with volume and quality targets and reporting against them.
Experience operating autonomously across multiple teams, with demonstrated critical thinking and thought leadership.
Experience building relationships with non-technical stakeholders and senior partners across functions.
Organizational, coordination, and multitasking experience.
Analytical and problem-solving experience, including defining metrics and building dashboards to track progress.
Experience working with product and engineering teams to translate user friction into product requirements.

Nice To Haves

Experience running data collection, annotation, or human-in-the-loop programs at scale.
Experience designing onboarding or enablement motions that scale to new teams without bespoke support.
Experience running programs with external or cross-functional contributors, such as expert networks, user research panels, or annotation vendors.
Familiarity with data privacy and compliance handling for sensitive workflows.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ongoing AI skill development, such as prompt/context engineering or agent orchestration, and staying current with emerging AI technologies.

Responsibilities

Run the expert engagement lifecycle, including identification, onboarding, scheduling, and capture, so experts can progress from nomination to completed work smoothly.
Plan and run recurring capture cycles, setting volume and quality targets by function, tracking progress on dashboards, and driving week-over-week progress.
Own the workflow validation process with experts to ensure workflows are accurate, correctly scoped, and ready for capture.
Manage partner communications.
Own intake and prioritization of inbound partner requests, route work to the appropriate team, and provide partners with a single point of entry.
Run quality reviews of captured expert work, apply learnings to subsequent cycles, and route issues to the appropriate owner.
Build self-serve onboarding resources, including playbooks, guides, and tooling, so a new function can get started in under a week.
Track expert contributions and validations by function, report against targets, and surface risks early.
Partner with Engineering and Product on capture tooling, ensure it works for non-engineering experts, and represent expert feedback as product requirements.
Ensure participation is opt-in and sensitive workflows are captured within privacy and compliance guardrails, working with privacy and legal partners.
Own the qualitative feedback loop and build the Voice of Customer program by collecting input from experts and partner teams, routing it to the right owners, and tracking it to resolution.