Content Automation Specialist Job Redmond area,Washington USA,Quality Assurance

This is an exciting opportunity to join a leading organization that is at the forefront of digital innovation, shaping the future of how people interact with technology. As an Aquent talent, you will play a pivotal role in advancing cutting‑edge AI experiences, contributing to a mission‑driven team focused on creating seamless and intelligent digital interactions. Your work will directly influence the quality and efficiency of widely used platforms, impacting millions of users globally.

We are seeking a highly technical and strategic individual to transform how content quality is validated across various digital experiences. In this dynamic role, you will be instrumental in designing scalable evaluation systems, pioneering automated testing workflows, and developing AI‑assisted quality frameworks that dramatically increase efficiency while upholding the highest human‑centered quality standards. You will be at the intersection of automation and human judgment, determining where technology can revolutionize processes and where human insight remains critical, ultimately building systems that continuously elevate content quality will partner with cross‑functional teams, defining testing strategies, building robust evaluation frameworks, identifying automation opportunities, and shaping the future of content quality operations.

What you’ll do:

Quality Systems Strategy:
- Design scalable testing and evaluation frameworks for content, templates, and AI‑generated experiences.
- Define quality measurement approaches and establish testing standards across diverse content ecosystems.
- Create recommendations for effectively balancing automation, AI evaluation, and essential human review.
Automation & Tooling:
- Develop and implement sophisticated automated testing workflows and validation systems.
- Build innovative tools and processes that significantly reduce manual effort while rigorously maintaining content quality.
- Identify and leverage opportunities to integrate AI for enhanced defect detection, content validation, and quality assurance.
Human Evaluation & AI Quality:
- Design robust human‑in‑the‑loop evaluation frameworks for accurately assessing AI outputs.
- Establish clear quality rubrics, comprehensive benchmarking criteria, and effective testing methodologies.
- Strategically determine where human judgment adds measurable value and where automation can efficiently scale operations.
Data & Optimization:
- Analyze complex testing metrics and operational data to pinpoint critical improvement opportunities.
- Develop actionable recommendations that enhance quality, boost efficiency, and expand testing coverage.
- Measure the effectiveness of testing systems and continuously optimize workflows for peak performance.
Cross‑Functional Leadership:
- Collaborate with cross‑functional teams on automation recommendations and thorough evaluations of quality risks.
- Drive the adoption of consistent testing standards and scalable evaluation practices across teams.
- Influence the long‑term strategy for content quality and AI evaluation programs, leaving a lasting impact.

Must‑Have

Qualifications:

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, AI, or a related field.
2‑4 years of experience in test automation, quality engineering, AI evaluation, or systems development.
Strong experience with Python and various automation tooling.
Experience with 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.

Nice‑to‑Have

Qualifications:

Experience evaluating generative AI systems or large language model (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 productivity software ecosystems.
Experience building internal tools, dashboards, or quality monitoring systems.

Compensation is based on several factors…