Quality Coordination Lead – AI Operations

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Responsible for client-specific quality programs, performance metrics, and escalations while facilitating team development and cross-functional collaboration.

• Develop client QA strategies (sampling design, audit methodologies, acceptance thresholds) and adjust to changes in scope and volume.

• Conduct root-cause analyses; implement CAPA plans with designated owners, timelines, and effectiveness evaluations.

• Organize training and certification for raters/annotators and coordinators; monitor completion and impact.

• Maintain performance dashboards (throughput, accuracy, productivity, cost) and translate insights into actionable steps.

• Handle client escalations; provide options, trade-offs, and recovery strategies.

• Standardize SOPs, templates, and checklists; eliminate bottlenecks.

• Initiate small automation projects (macros, templates, RPA/API handoffs) with Ops Tech; scale successful initiatives.

• Mentor teams on tools, workflows, and QA best practices.

• Ensure compliance and security in data handling and platform access.

⛳️ Requirements

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

• Over 2 years of experience in quality operations with practical QA and workforce/training coordination.

• More than 1 year of experience in leading teams/pods (formally or informally).

• Experience in multi-project planning and managing stakeholders.

• Strong client communication skills and participation in governance cadence.

• Proficiency in spreadsheets, project management/task boards, and basic business intelligence; familiarity with ETL is a bonus.

• Experience in capacity planning with vendors; confident in escalation and negotiation.

• Proven effectiveness in global, distributed teams.

• Near-native English proficiency with strong writing and editorial abilities.

• Familiarity with generative AI tools (text/voice/video).

• Background in QA testing, rubric design, or evaluating AI safety/ethics.

• Knowledge of data-annotation platforms and model-evaluation tools.

• Ability to conceptualize code/datasets/workflows (coding skills are not required).

• Demonstrated ability to work independently and manage workflows efficiently in a remote environment.

• Multilingual capabilities beyond English.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Professional development opportunities