Lead Quality Manager - Generative AI Data Quality

Key Responsibilities

• Set program quality goals, roadmap, and operating rhythms (cadence, audit plan, reviews). 
• Manage a team of Analysts and Coordinators; hire, coach, and run performance cycles. 
• Co-own client governance with Ops; align on scope, priorities, and changes. 
• Standardize SOPs/rubrics; oversee training/certification paths and knowledge base. 
• Define core dashboards/metrics; drive actions for speed, quality, and cost. 
• Champion compliance, privacy, and security; ensure audit readiness. 
• Coordinate with Vendor Management on SLAs, capacity, and improvement plans. 
• Sponsor automation pilots and scale proven solutions with Ops Tech/Product. 
• Own risk management at program level; ensure documented CAPA with follow-through. 
• Build succession pipelines and skills matrices for the team. 
 

Skills

• Program planning and portfolio governance. 
• People leadership (goals, coaching, delegation, feedback). 
• Senior client communication and negotiation. 
• Strong spreadsheets/BI; SQL/ETL familiarity is a plus. 
• Quality systems (SOPs, QA gates, acceptance criteria) and compliance expertise. 

Scope and Autonomy

• Manages a single program/team end-to-end; sets standards and rhythms. 
• Makes day-to-day and tactical strategic decisions; escalates only high-impact items. 
• Partners with Operations Manager on client outcomes and team performance. 

Education and Experience

• Bachelor’s degree or equivalent experience in Business, Operations, Quality, or Data/Engineering. 
• 3–5 years in quality/ops; 3–5 years managing teams or multi-workstreams.