Role Overview

Lead client-specific quality programs, performance metrics, training, and escalations across multiple AI data and evaluation projects. The role shares accountability for client and team performance with the Operations Manager.

Key Responsibilities

• Develop and adapt client QA strategies, sampling methods, audits, and acceptance thresholds.

• Conduct root-cause analysis and drive CAPA plans.

• Plan and track rater/annotator training and certification.

• Monitor performance, accuracy, productivity, throughput, and cost metrics.

• Manage client escalations and recommend recovery actions.

• Standardize SOPs, templates, and QA processes.

• Support automation initiatives with Operations Technology teams.

• Coach teams on tools, workflows, and QA practices.

• Ensure data-handling and platform-access compliance.

Requirements

• Bachelor’s degree or equivalent experience in Business, Operations, Quality, Data, or Engineering.

• 2+ years in quality/operations with hands-on QA and workforce/training coordination.

• 1+ year leading people or teams.

• Strong project planning, stakeholder management, spreadsheets, task-management tools, and basic BI skills.

• Experience with capacity planning, vendors, escalation, and negotiation.

• Ability to work effectively with global, distributed teams.

• Near-native English with strong writing and editorial skills.

• Hands-on experience with generative AI tools.

• Background in QA testing, rubric design, AI safety/ethics evaluation, data annotation, or model evaluation is an advantage.

• Ability to understand code, datasets, and workflows at a conceptual level; coding is not required.

• Ability to work independently in a remote environment.

• Multilingual ability beyond English is an advantage.