Program Manager - Content Automation Specialist

163086-1

Job Title: Program Manager - Content Automation Specialist

Location: Remote (Pacific Time hours)

Rate: $38-$40 per hour

Duration: 8/3/2026 to 12/31/2026 (Potential for contract extension)

This role focuses on transforming how content quality is validated across AI-powered productivity tools and digital experiences. The Content Automation Specialist will design and implement scalable evaluation systems, automated testing frameworks, and AI-assisted quality methodologies. The objective is to increase operational efficiency while maintaining high standards of human-centered quality. This position plays a key role in advancing content quality practices by identifying where automation can replace manual review, defining where human evaluation remains critical, and building systems that continuously improve quality at scale.

Required Skills & Qualifications

Education

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Artificial Intelligence, or a related technical field

Experience

• Background in test automation, quality engineering, AI evaluation, or systems development
• Experience building testing frameworks, automation workflows, or quality systems
• Demonstrated ability to translate data insights into actionable recommendations

Core Skills

• Strong proficiency in Python and automation tooling
• Experience with AI development and productivity tools such as code editors or AI-assisted platforms
• Strong systems-thinking and technical problem-solving capabilities
• Ability to define scalable processes and frameworks
• Experience working with data to drive decision-making and optimization

Candidate Requirements

• Demonstrated stability in prior roles
• Ability to clearly communicate technical concepts and past project experience
• Availability to work standard Pacific Time hours in a remote environment
• Supplier-provided equipment required (standard PC)

Assessment Process

• 1 to 2 interview rounds (30 to 45 minutes each)
• Interviews include technical discussions and review of prior experience
• Candidates are expected to articulate hands-on experience with automation, AI tooling, and quality frameworks

Performance Measurement

Success in this role will be evaluated based on:

• Automation efficiency and measurable reduction in manual effort
• Quality and usability of automation solutions
• Delivery against milestones and timelines
• Effectiveness of recommendations and ability to drive implementation
• Communication of risks, blockers, and progress updates

Unique Selling Points

• Opportunity to shape how AI-generated content is evaluated and improved at scale within advanced digital ecosystems
• Direct impact on automation strategies, quality frameworks, and user experience outcomes
• Exposure to cutting-edge AI tooling, content evaluation systems, and large-scale quality operations
• Influence cross-functional decision-making related to automation, human evaluation, and quality standards
• Work in a highly visible role focused on innovation, efficiency, and scalable impact

Key Responsibilities

Quality Systems Strategy

• Design scalable testing and evaluation frameworks for content, templates, prompt libraries, and AI-generated outputs
• Define quality measurement approaches and establish testing standards across content ecosystems
• Recommend optimal balance between automation, AI-driven evaluation, and human review

Automation and Tooling

• Develop automated testing workflows and validation systems
• Build tools and processes that reduce manual effort while maintaining content integrity
• Identify opportunities to apply AI for defect detection, content validation, and quality assurance

Human Evaluation and AI Quality

• Design human-in-the-loop evaluation frameworks for AI-generated content
• Establish quality rubrics, benchmarking criteria, and testing methodologies
• Determine where human judgment adds measurable value versus scalable automation

Data and Optimization

• Analyze testing metrics and operational data to identify improvement opportunities
• Provide actionable recommendations to improve quality, efficiency, and coverage
• Continuously optimize workflows based on performance insights

Cross-Functional Collaboration

• Partner with cross-functional stakeholders to evaluate quality risks and automation opportunities
• Drive adoption of testing standards and scalable evaluation practices
• Influence long-term strategies for content quality and AI evaluation