Project Manager Generative AI Operations
About the role
The Quality, Workforce & Training Lead (AI Data Operations) oversees quality assurance, workforce planning, and training programs for AI training data delivery on multiple small projects or one large strategic project. They improve performance, compliance, and processes across multiple projects, partnering with the Senior Quality Analyst to share accountability for client outcomes and team performance.
Job Responsibilities
- Owns quality assurance, workforce planning, and training programs for AI training data delivery on multiple small projects or one large strategic project.
- Improves performance, compliance, and processes across multiple projects.
- Pairs with the Senior Quality Analyst to share accountability for client outcomes and team performance.
Key Responsibilities
- Quality Assurance: Monitor QA plans, track defects risks, lead corrective actions, and prevent recurrences.
- Workforce Planning: Forecast capacity needs, schedule shifts, align vendors and internal teams.
- Training Programs: Build and deliver training and certification for raters/annotators; update materials.
- Performance Management: Maintain dashboards for throughput, quality, productivity, and cost.
- Compliance & Security: Ensure policy adherence on data handling, privacy, safety; support audits.
- Process Improvement: Standardize SOPs, remove bottlenecks, pilot changes.
- Stakeholder & Client Support: Join client reviews, explain quality results and risks.
- Team Development: Coach Coordinators and Associate PMs; support onboarding and skills growth.
- Team Management: Manage attendance, performance reviews, contract renewals.
- Risk & Change Control: Maintain risk/issue logs, manage change requests, escalate high-impact items.
Required Skills
- Planning and organization across multiple projects.
- Clear communication with clients and internal partners.
- Solid use of spreadsheets, PM/task boards, and basic BI; familiarity with ETL concepts is a plus.
- Practical QA know-how (sampling, audits, acceptance criteria).
- Capacity planning, scheduling, and vendor coordination.
- Coaching for Coordinators.
- Confident escalation and negotiation skills.
- Comfortable working with global, distributed teams (intermediate to advanced English).
Additional Qualifications (Preferred)
- Near-native English with strong writing and editorial skills.
- Hands-on experience with generative AI tools (text, voice, or video).
- Background in QA testing, rubric design, or AI safety/ethics evaluation.
- Familiarity with data-annotation platforms and model-evaluation tools.
- Able to interpret code, datasets, and system workflows at a conceptual level.
- Able to work independently in a remote environment.
- Multilingual ability beyond English.
Scope and Autonomy
Leads quality, workforce, and training programs across multiple projects. Works independently within scope, budget, compliance, and quality guardrails. Shares accountability for client results and team performance with the Quality Manager.
Experience and Education
- 2+ years in project/operations delivery with hands-on QA and workforce planning (AI data, content review, labeling/annotation, or adjacent domains).
- Experience running trainings and coordinating multi-team delivery.
- Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields.
Hiring Process Note
We may use AI tools to support parts of the hiring process, but final decisions are made by humans.
Job Details
Location: Remote, Santa Clara, CA
Job Type: remote
Posted: May 5, 2026
Categories: Data Annotation
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