Program Manager, Human Data Operations

mpathic•Seattle or San Francisco Bay Area preferred, CA

About The Position

mpathic is seeking a Program Manager, Human Data Operations to lead the execution of complex AI safety, evaluation, human data and red teaming for leading AI companies. You will report directly to the Co-Founder/Chief Innovation Officer. This role owns end-to-end delivery across cross-functional project teams and is accountable for project execution, quality, stakeholder communication, and customer outcomes. The ideal candidate has significant experience managing large-scale services operations, including distributed teams of experts, annotators, reviewers, red teamers, contractors, and quality assurance personnel. They are comfortable operating in fast-paced startup environments where priorities evolve quickly and successful delivery requires proactive communication, operational rigor, and strong judgment. You will act as the connective tissue between Data Services, QA, Engineering, AI/ML, Product, Data Science, and customer-facing teams—translating ambiguous customer and operational needs into dependable delivery, and keeping the many people involved aligned around what we are building and why. This is a role about both execution and leadership. You should be as comfortable coordinating distributed expert workflows and managing customer expectations as you are building systems that improve project visibility, quality, and throughput. You will start as a hands-on individual contributor owning your delivery pod, with room to shape how program management scales here as the team grows.

Requirements

5+ years of program management, project delivery, operations leadership, or related experience.
Demonstrated experience managing large-scale human data, annotation, evaluation, trust & safety, research operations, or expert-driven workflows.
Experience leading distributed teams of contractors, reviewers, annotators, experts, or QA personnel.
Experience managing customer-facing programs with executive stakeholders.
Experience operating in startup or high-growth environments.

Nice To Haves

PMP, PgMP, CAPM, Agile, Scrum, Lean, or equivalent project management certification strongly preferred.
Experience with AI safety, LLM evaluation, red teaming, human-in-the-loop systems, or trust & safety operations.
Experience building scalable operational systems and quality management processes.

Responsibilities

Own Project Execution, Contract Handoff to Final Delivery (Core)
Be the single operational lead for the delivery pods you own, carrying each program from intake through staffing, execution, quality review, and customer sign-off.
Build and coordinate project teams
Establish project plans, staffing models, timelines, communication cadences, and risk mitigation plans.
Monitor project performance, utilization, throughput, quality metrics, and budget performance.
Manage Customer Relationships & Delivery Milestones
Manage customer expectations and delivery milestones throughout the engagement lifecycle.
Lead internal project meetings, status reviews, and customer-facing reporting cadences.
Identify expansion opportunities and surface operational improvements to leadership.
Build Quality & Operational Systems
Define what “good” means for the programs you own, and the quality controls and QA processes that measure it.
Set annotation and human-data quality standards that are consistent, auditable, and humane for the people doing the work.
Build scalable operational systems that improve project visibility, quality, or throughput across the Human Data team.
Capture Inputs from Customers & Delivery Teams
Partner with pre-sales and customer-facing teams to translate customer requirements into executable delivery plans.
Bring front-line delivery insights into capacity planning and operational improvement on purpose.
Turn what you learn into systemic improvements rather than one-off workarounds.
Be the Connective Tissue
Keep Human Data, QA, Engineering, Product, Research, and Customer Success aligned on what is being delivered and why.
Translate between operational, technical, and commercial perspectives so the right tradeoffs get made.