Quality Assurance Manager overseeing quality assurance, workforce planning, and training for AI data operations. Improving processes and compliance on multiple projects in India.
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.
Monitor QA plans in partnership with Quality team (sampling, audits, acceptance criteria).
Track risks of defects, lead corrective actions, and prevent recurrences.
Forecast capacity needs; schedule shifts and handoffs; align vendors and internal teams to meet volume and turnaround targets.
Build and deliver training and certification for raters/annotators and coordinators; update materials as guidelines change.
Maintain dashboards for throughput, quality, productivity, and cost; turn data into clear actions for improvement.
Ensure policy adherence on data handling, privacy, safety, and platform access; support audits and remediation.
Standardize SOPs and checklists; remove bottlenecks; pilot small changes that improve speed, quality, or cost.
Join client reviews with the Quality Manager and PMs; explain quality results, risks, and next steps.
Coach Coordinators (C2–C3) and Associate PMs (P1) on QA, workflows, and tools; support onboarding and skills growth.
Keep risk/issue logs; manage change requests that impact quality, capacity, or training; escalate high-impact items with options.
Requirements
Bachelor’s degree or equivalent experience in business, data/operations, engineering, or related fields
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
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).
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