Project Coordinator- Generative AI Data Operations

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. Partners with the Senior Quality Analyst to share accountability for client outcomes and team performance. "Owns quality, workforce, and training programs that scale Generative AI data operations, driving performance, compliance, and process improvement across a project."

Key Responsibilities

• Quality Assurance: Monitor QA plans in partnership with Quality team (sampling, audits, acceptance criteria). Track risks of defects, lead corrective actions, and prevent recurrences.
• Workforce Planning: Forecast capacity needs; schedule shifts and handoffs; align vendors and internal teams to meet volume and turnaround targets.
• Training Programs: Build and deliver training and certification for raters/annotators and coordinators; update materials as guidelines change.
• Performance Management: Maintain dashboards for throughput, quality, productivity, and cost; turn data into clear actions for improvement.
• Compliance & Security: Ensure policy adherence on data handling, privacy, safety, and platform access; support audits and remediation.
• Process Improvement: Standardize SOPs and checklists; remove bottlenecks; pilot small changes that improve speed, quality, or cost.
• Stakeholder & Client Support: Join client reviews with the Quality Manager and PMs; explain quality results, risks, and next steps.
• Team Development: Coach Coordinators (C2–C3) and Associate PMs (P1) on QA, workflows, and tools; support onboarding and skills growth.
• Team Management: Manage employee attendance, conduct individual performance reviews and support contract renewals.
• Risk & Change Control: Keep risk/issue logs; manage change requests that impact quality, capacity, or training; elevate high-impact items with options.

Education

• Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields

Experience

• 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

Skills

• Planning and organization across multiple projects (quality, workforce, and training tracks)
• Clear communication with clients and internal partners; confident in reviews and governance forums
• 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) and continuous‑improvement mindset
• Capacity planning, scheduling, and vendor coordination
• Coaching for C2–C3 Coordinators and P1s; gives day‑to‑day guidance
• Confident escalation and negotiation to resolve risks, issues, and scope questions
• Comfortable working with global, distributed teams (intermediate to advanced English)

Additional Qualifications (P1+)

• 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
• Ability to interpret code, datasets, and system workflows at a conceptual level (no coding required)
• Able to work independently and manage workflows effectively in a remote environment
• Multilingual ability beyond English

Scope & Autonomy (P2 Alignment)

• Leads quality, workforce, and training programs across multiple projects; influences delivery outcomes without formal line management
• Works independently within scope, budget, compliance, and quality guardrails; escalates exceptions
• Shares accountability for client results and team performance with the Quality Manager