Senior Manager, AI Data Operations

Career Guide

A Senior Manager, AI Data Operations leads teams that produce, improve, and govern the data used to train and evaluate AI systems. The role focuses on building reliable workflows for data collection, labeling, quality checks, and delivery, while meeting speed, cost, and compliance goals.

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Key Responsibilities

Set strategy for AI data production across multiple projects and model teams
Design end to end workflows for data sourcing, labeling, review, and delivery
Lead and develop managers, team leads, and large groups of data specialists
Define quality standards and acceptance criteria for training and evaluation datasets
Build measurement systems for throughput, accuracy, cost, and cycle time
Partner with product, engineering, and research teams to translate model needs into data tasks
Create clear documentation, guidelines, and training for consistent labeling decisions
Manage vendors and outsourced teams, including contracts, performance, and capacity planning
Establish data governance practices for access control, privacy, and audit readiness
Identify automation opportunities and guide tooling improvements with engineering
Run risk management for data issues such as bias, leakage, and duplication
Report progress and outcomes to senior stakeholders and executives

Top Skills for Success

People Leadership

Stakeholder Management

Program Management

Process Design

Operational Metrics

Quality Management

Vendor Management

Data Governance

Privacy Compliance

Data Labeling Operations

Annotation Guidelines

Inter Annotator Agreement

Dataset Curation

Data Sampling Strategy

Model Evaluation Support

Bias Risk Management

Career Progression

Can Lead To

AI Operations Director

Head of AI Data

Director of Data Operations

Director of Trust and Safety Operations

Director of Data Governance

Transition Opportunities

Product Operations Lead for AI

Technical Program Manager for ML platforms

Data Product Manager

ML Operations Manager

Responsible AI Program Lead

Common Skill Gaps

Often Missing Skills

Cost ModelingCapacity PlanningExperiment DesignPrompt Evaluation OperationsData Lineage TrackingAutomation RoadmappingBenchmark DesignIncident Management

Development SuggestionsBuild a simple operational scorecard with cost, speed, and quality targets. Run small controlled pilots to compare labeling approaches. Partner with engineering to add basic data lineage and audit trails. Practice executive updates that connect data outcomes to model performance and business impact.

Market Intelligence Report

Senior Manager, AI Data Operations is part of the Program Management 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 LevelNot typical for this role

Mid LevelUSD 150,000 to 200,000

Senior LevelUSD 200,000 to 280,000

Growth Trend

Growing demand, driven by increased investment in generative AI, higher expectations for data quality, and scaling needs for human and automated review operations.

Companies Hiring

Major Employers

OpenAIGoogleMicrosoftAmazonMetaAppleNVIDIAAnthropicCohereScale AIDataBricksIBMSalesforceTikTokTesla

Industry Sectors

Artificial IntelligenceCloud ComputingEnterprise SoftwareEcommerceConsumer TechnologyAutonomous VehiclesFinancial ServicesHealthcare TechnologyMedia and Entertainment

Recommended Next Steps

Create a portfolio of two to three scaled data operations case studies with metrics and outcomes

Strengthen hiring plans with role definitions, leveling, and interview rubrics

Implement a quality system with sampling, audits, and root cause analysis

Standardize guideline writing and change control for labeling decisions

Develop a vendor playbook covering selection, onboarding, and performance management

Align with legal and security partners on privacy, retention, and access controls

Build a quarterly roadmap that balances throughput, quality, and automation improvements