AI Evaluation Operations Manager

Career Guide

An AI Evaluation Operations Manager builds and runs the day to day systems that measure how well AI products perform. The role focuses on reliable testing workflows, clear quality standards, and smooth coordination between people, processes, and tools so evaluation results are trusted and delivered on time.

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Key Responsibilities

Define evaluation goals and success metrics with product and research partners
Create and maintain evaluation workflows from test design to final reporting
Set quality standards for evaluation data and reviewer decisions
Hire, train, and manage evaluation teams and vendors
Design reviewer guidelines and calibration routines to improve consistency
Plan capacity and staffing to meet launch and research timelines
Track operational metrics such as turnaround time, consistency, and coverage
Manage evaluation tooling needs and coordinate improvements with engineering
Run incident response for quality issues and implement root cause fixes
Communicate evaluation status and risks to stakeholders in a clear, regular cadence
Support compliance requirements related to data handling and access
Document processes so evaluation work is repeatable and auditable

Top Skills for Success

Program Management

Stakeholder Management

Process Design

People Management

Vendor Management

Risk Management

Quality Management

Data Fluency

Experiment Design

Model Evaluation

Prompt Testing

Annotation Operations

Reviewer Calibration

Guideline Writing

Tooling Requirements

Metric Definition

Workflow Automation

Privacy And Data Handling

Career Progression

Can Lead To

AI Evaluation Lead

AI Quality Manager

AI Operations Director

Responsible AI Program Manager Trust And Safety Operations Manager

Transition Opportunities

Product Operations Manager Technical Program Manager Data Operations Manager Machine Learning Program Manager Product Manager

Common Skill Gaps

Often Missing Skills

Evaluation Metric DesignReviewer CalibrationData Quality AuditingTooling SpecificationExperiment DesignPrivacy And Data HandlingRoot Cause Analysis

Development SuggestionsBuild hands on practice by running a small evaluation program end to end. Write clear guidelines, calibrate reviewers weekly, and track consistency. Learn to define metrics that match product goals, and partner closely with engineering to translate process needs into tool requirements. Strengthen data handling habits by following least access and documenting data flows.

Market Intelligence Report

AI Evaluation Operations Manager is part of the Product Operations category.Explore our market intelligence report to see how AI and hiring demand are shifting for these roles.

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Salary & Demand

Median Salary Range

Entry Level$95,000 to $125,000

Mid Level$125,000 to $170,000

Senior Level$170,000 to $230,000

Growth Trend

Growing quickly as more companies ship AI features and need repeatable, high quality evaluation operations. Demand is strongest in tech, enterprise software, and AI focused startups.

Companies Hiring

Major Employers

OpenAIGoogleMicrosoftMetaAmazonAppleAnthropicCohereScale AIByteDance

Industry Sectors

Consumer TechnologyEnterprise SoftwareCloud PlatformsAI Research LabsCustomer Support TechnologySearch And AdvertisingEcommerceFintechHealthcare TechnologyEducation Technology

Recommended Next Steps

Create a portfolio example of an evaluation workflow with goals, metrics, guidelines, and reporting

Practice building a calibration plan and measuring reviewer consistency over time

Develop a simple dashboard that tracks turnaround time, error rates, and coverage

Draft a one page evaluation plan for a real AI feature and review it with peers

Strengthen vendor management skills by creating a statement of work template and quality checks

Learn incident management basics and write a playbook for evaluation quality issues

Update your resume to highlight operations outcomes such as cycle time reduction and quality improvements