TPM - SME Onboarding, Engagement and Voice of Customer

The ATA XFN team builds the data flywheel that makes Meta's first-party models measurably better at cross-functional professional work. We capture how Meta's strongest teammates in Finance, Legal, People, Sales, and beyond, actually do their work, structure it into Skills and training-ready data, and feed it into first-party model training.

None of that happens without Subject Matter Experts(SMEs). This TPM runs the SME Onboarding, Engagement and Voice of Customer workstream: the end-to-end motion that takes a prioritized workflow, finds the right expert, gets their work captured at quality, and turns each batch into results our partners can see, and get SME feedback to improve the products and processes. The role is the operational engine of the program and the primary interface to our partner organizations. Success looks like a repeatable engagement machine that scales batch over batch without the team hand-holding every expert.

Responsibilities

• Run the SME engagement lifecycle end to end: identification, onboarding, scheduling, and capture, so experts move from nomination to completed demonstration without friction.
• Plan and run recording batches: define the batch plan, set volume and quality targets by domain, track progress on a dashboard, and drive week over week velocity without last-day surges.
• Own the workflow validation process with SMEs, so validated workflows are accurate, correctly grained, and ready for capture.
• Manage partner communications: roadmaps, batch results, and regular updates to ATA XFN pod POCs and partner function leads.
• Own intake and prioritization of inbound partner requests, routing work to the right domain workstream and keeping one front door for partners.
• Run quality reviews of captured demonstrations, drive follow-up learnings into the next batch, and route failures back to the right owner.
• Build the self-serve onboarding path: playbooks, guides, and tooling that let a new function get started in under a week.
• Track demonstrations and validations per batch by domain, report against targets, and surface risks early.
• Partner with Engineering and Product on capture tooling, so the experience works for non-engineer experts, and represent SME feedback as product requirements.
• Ensure sensitive workflows are captured within privacy and compliance guardrails, working with privacy tooling and review partners.
• Own the qualitative feedback loop and stand-up the “Voice of Customer” workstream: collect input from experts and partner teams, route it to the right owners, and track it to resolution, so the program improves based on real experience.

Minimum qualifications

• Bachelor of Computer Science or a related technical discipline, or equivalent experience
• 7+ years of software engineering, systems engineering, hardware engineering, or technical product/program management experience
• 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 multi-tasking 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

Preferred qualifications

• 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
• 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 (for example efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (for example risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (for example prompt and context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies