Verified Job
IT / Software / Data Analyst
Software Engineer II – GenAI Quality Engineering- job post Electronic Arts 3.8 3.8 out of 5 stars Va
IT / Software / Data Analyst
#782072
Remote / WFH
Electronic Arts
Job Description
Full job description
General Information
Locations: Vancouver, British Columbia, Canada
Role ID
215862
Worker Type
Regular Employee
Studio/Department
EA Studios - Quality Verification
Work Model
Hybrid
Description & Requirements
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
About the Role
The EA SPORTS FC Quality Verification Engineering team partners closely with Quality Verification and Development teams to deliver high-quality player experiences through innovative automation and engineering. As a Software Engineer II specializing in Generative AI, you will build AI-powered quality solutions that improve test automation, content validation, and development workflows. This is an opportunity to solve complex engineering challenges at the intersection of AI, automation, and game development while helping enable the next generation of player and creator experiences.
What You'll Do
Design and develop AI-powered quality engineering solutions using LLMs and intelligent automation.
Build automated workflows that generate, execute, and maintain tests for user-generated and procedurally generated content.
Develop scalable validation systems that verify content quality, stability, performance, and integrity throughout the development pipeline.
Integrate automated quality checks into content creation tools and workflows to identify issues early in the development process.
Partner with software engineers, technical artists, and cross-functional teams to embed quality engineering into development pipelines.
Create automation frameworks that improve test coverage and reduce reliance on manual testing.
Continuously improve AI models, testing frameworks, and engineering tools to increase efficiency, reliability, and scalability.
General Information
Locations: Vancouver, British Columbia, Canada
Role ID
215862
Worker Type
Regular Employee
Studio/Department
EA Studios - Quality Verification
Work Model
Hybrid
Description & Requirements
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
About the Role
The EA SPORTS FC Quality Verification Engineering team partners closely with Quality Verification and Development teams to deliver high-quality player experiences through innovative automation and engineering. As a Software Engineer II specializing in Generative AI, you will build AI-powered quality solutions that improve test automation, content validation, and development workflows. This is an opportunity to solve complex engineering challenges at the intersection of AI, automation, and game development while helping enable the next generation of player and creator experiences.
What You'll Do
Design and develop AI-powered quality engineering solutions using LLMs and intelligent automation.
Build automated workflows that generate, execute, and maintain tests for user-generated and procedurally generated content.
Develop scalable validation systems that verify content quality, stability, performance, and integrity throughout the development pipeline.
Integrate automated quality checks into content creation tools and workflows to identify issues early in the development process.
Partner with software engineers, technical artists, and cross-functional teams to embed quality engineering into development pipelines.
Create automation frameworks that improve test coverage and reduce reliance on manual testing.
Continuously improve AI models, testing frameworks, and engineering tools to increase efficiency, reliability, and scalability.
