Requirement - Content Automation Specialist Location- 100% Remote Contract W2 Ex- Microsoft Must ... Required Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science ...
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Requirement - Content Automation Specialist Location- 100% Remote Contract W2 Ex- Microsoft Must ... Required Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science ...
Quick apply
Requirement - Content Automation Specialist Location- 100% Remote Contract W2 Ex- Microsoft Must ... Required Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science ...
| Aspect | Remote Amazon Computer Science | Remote Amazon Software Development |
|---|---|---|
| Required Credentials | Bachelor's in Computer Science or related field, possibly some certifications | Bachelor's in Computer Science or related field, often with coding certifications |
| Work Environment | Research, data analysis, algorithm design, theoretical work | Code writing, application development, system implementation |
| Employer & Industry Usage | Amazon research labs, data teams, algorithm groups | Amazon software engineering teams, product development |
| Common Search & Comparison Intent | Understanding research roles vs development roles at Amazon | Distinguishing between development and research positions at Amazon |
Remote Amazon Computer Science roles focus on research, algorithms, and theoretical work, while Remote Amazon Software Development roles emphasize coding, application building, and system implementation. Both require a strong foundation in computer science but differ in daily tasks and work environment.
Requirement - Content Automation Specialist
Location- 100% Remote
Contract W2
Ex- Microsoft
Must Haves:
Python
Testing Framework
Some AI knowledge
Job Description:
Overview
We are seeking a highly technical and strategic Content Automation Specialist to transform how content quality is validated across Microsoft 365 and Copilot experiences.
This role focuses on designing scalable evaluation systems, automated testing workflows, and AI-assisted quality frameworks that increase efficiency while maintaining human-centered quality standards. The ideal candidate understands where automation can replace manual review, where human evaluation remains critical, and how to build systems that continuously improve content quality at scale.
This individual will partner with cross-functional teams to define testing strategies, build evaluation frameworks, develop automation opportunities, and shape the future of content quality operations.
Responsibilities
Quality Systems Strategy
• Design scalable testing and evaluation frameworks for content, templates, prompt templates, and AI-generated experiences.
• Define quality measurement approaches and establish testing standards across content ecosystems.
• Create recommendations for balancing automation, AI evaluation, and human review.
Automation & Tooling
• Develop and implement automated testing workflows and validation systems.
• Build tools and processes that reduce manual effort while maintaining content quality.
• Identify opportunities to leverage AI for defect detection, content validation, and quality assurance.
Human Evaluation & AI Quality
• Design human-in-the-loop evaluation frameworks for assessing AI outputs.
• Establish quality rubrics, benchmarking criteria, and testing methodologies.
• Determine where human judgment adds measurable value and where automation can scale operations.
Data & Optimization
• Analyze testing metrics and operational data to identify improvement opportunities.
• Develop recommendations that improve quality, efficiency, and testing coverage.
• Measure the effectiveness of testing systems and continuously optimize workflows.
Cross-Functional Leadership
• Partner with cross-functional teams on automation recommendations and evaluations of quality risks.
• Drive adoption of testing standards and scalable evaluation practices.
• Influence long-term strategy for content quality and AI evaluation programs.
Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, AI, or related field.
• 2-4 years of experience in test automation, quality engineering, AI evaluation, or systems development.
• Strong experience with Python and automation tooling.
• Experience with Copilot, VSCode, and other AI tooling and infrastructure.
• Experience building testing frameworks, quality systems, or workflow automation solutions.
• Experience interpreting data and translating findings into strategic recommendations.
• Strong technical problem-solving and systems-thinking skills.
Preferred Qualifications
• Experience evaluating generative AI systems or LLM-powered products.
• Experience designing human evaluation programs or human-in-the-loop workflows.
• Familiarity with content quality measurement and content operations.
• Experience working with machine learning, AI quality, or model evaluation frameworks.
• Understanding of Microsoft 365, Copilot, or productivity software ecosystems.
• Experience building internal tools, dashboards, or quality monitoring systems.
Sourced by ZipRecruiter
51 - 200 Employees
Fort Mill, SC, US
2015