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AI Enablement Engineer

Job in Vancouver, BC, Canada
Listing for: Electronic Arts
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 CAD Yearly CAD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
  • Location:

    Austin
  • Country:
    United States of America

Worker Type:
Regular Employee

Studio/Department:
Other

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.

Our EA Experiences group (XO) is dedicated to ensuring great experiences for our growing communities centered around our world-renowned brands, including fan-favorites like Apex, Battlefield, EA SPORTS FC, Madden NFL and The Sims, just to name a few. We’re a multi-functional group, with world-class expertise building fandoms, driving interactive storytelling, and positioning our franchises at the center of the broader entertainment ecosystem.

We inspire, connect, and engage fans through culturally relevant content, intentionally architected journeys across channels, and meaningful fan care. Our goal is to provide valuable, easy experiences that fans love – in our games, around our games, and through innovative adjacent experiences to grow and enrich how fans experience EA as we shape the future of entertainment.

To empower more players and fans in new and amazing ways, we need more innovators to join our world-class team. The future of entertainment is interactive, and you can help lead that future, by growing and enriching how hundreds of millions of people (and counting) find joy and belonging, forge friendships, and celebrate their lived experiences through the work we do every single day, together.

AI

Solutions Engineer | EA Experiences

As an AI Solutions Engineer for EA Experiences, you will be an innovator and creator of cutting‑edge AI solutions, solutions that keep our fans at the center of everything we do. You will collaborate closely with teams across EA Experiences, developing and understanding our business, their challenges, and their opportunities. You will rapidly create innovative AI solutions using cutting‑edge AI technologies that provide increased efficiency and help our teams focus on what matters most, our fans.

This is an internal enablement role focused on building and product ionizing GenAI solutions for XO teams.

Responsibilities
  • Implement AI solutions to enable efficiency, expansion, and transformation across EA Experiences, directly aligned with EA Experiences' goals.
  • Stay informed on the evolution of AI technologies and opportunities to drive efficiency, expansion, and transformation.
  • Have a deep understanding of AI technologies and solutions, specifically focusing on how they can be integrated into business processes and systems to enhance efficiency.
  • Collaborate with EA Experiences teams to understand their business, processes, opportunities, and challenges.
  • Identify opportunities for developing creative AI solutions that enable our teams to focus on creative and innovative work that keeps our fans at the center of what we do.
  • Be an AI evangelist, promoting the use of AI as a force‑multiplier.
Qualifications
  • 4+ years of experience rapidly prototyping and deploying robust production solutions incorporating software engineering, infrastructure, architectural, and security best practices.
  • Experience using agentic AI software engineering solutions such as Cursor, Git Hub CoPilot, or Claude Code.
  • Extensive experience engineering AI solutions and excellent working knowledge of prompt and context engineering, AI agents and agentic architectures, tool calling, and Model Context Protocol (MCP), AI assistants, RAG, embeddings, and vector databases, model tuning, evaluation, benchmarking, and guardrails.
  • An excellent understanding of architecture, design principles, and cloud services such as AWS (Azure and GCP cloud services are optional).
  • Enterprise architecture and microservices design.
  • Observability and telemetry.
  • Infrastructure as code and CI/CD.
  • Data science experience is beneficial.
  • Content production (e.g. marketing) is strongly beneficial.
  • Experience navigating the legal, ethical, and security implications for AI.
  • Thrives…
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