Project Manager

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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; escalate high-impact items with options. 

Additional Job Details:
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