Electronic Arts

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.

You will be the hands-on AI architect and engineer, reporting to the Head of AI Enablement for EA Experiences. You will design, create, and deploy AI-powered solutions that transform content creation, data and analytics, and transform our business processes and systems. You'll architect and ship innovative AI native solutions that leverage agents, multi-agent workflows, guardrails, knowledge bases, knowledge graphs, LLM's, vision models, diffusion models, and related technologies. You will define requirements, rapidly prototype, iterate with stakeholders, and establish reusable architectures, standards, and patterns using the latest AI engineering methodologies, models, tools, and platforms. You're creative, innovative, self-motivated, and team-first, equally strong at problem-solving and collaborating across creative, product, marketing, data, and engineering teams. You will create scalable AI pipelines and workflows that enable teams to spend more time on high-value, creative, and strategic work. You will be a hybrid worker, collaborating with teams 3 days a week from the office; international travel to collaborate with global teams is an added bonus.

Responsibilities:

• Architect end-to-end AI solutions: Design and implement AI-native solutions and multi-agent workflows that transform content creation, data and analytics, and core business processes, from idea through production deployment.

• Drive AI-enabled content creation: Build and evolve AI pipelines, assistants, and tools that help creative, marketing, and franchise teams ideate, generate, localize, and optimize content (image, video, copy, interactive experiences) at scale while staying on-brand and fan-first.

• Lead data, knowledge, and RAG architectures: Define and implement data lakes, vector stores, knowledge bases, and knowledge graphs to power intelligent assistants and solutions

• Productionize and integrate AI systems: Own the path from prototype to production—integrating AI solutions with existing platforms, services, and workflows, and defining observability, reliability, and performance baselines.

• Embed guardrails, safety, and governance: Implement guardrails, policies, and evaluation frameworks that address IP, privacy, security, safety, and bias; define acceptance criteria, red/amber/green thresholds, and incident handling for AI-powered systems.

• Standardize architectures, patterns, and tooling: Create and maintain reusable reference architectures, design patterns, SDKs, and templates for agents, multi-agent workflows, RAG, and LLM/vision/diffusion integrations to accelerate adoption across teams.

• Partner and co-create with cross-functional teams: Collaborate with creative, product, marketing, data, engineering, operations, and legal partners to identify high-value AI opportunities, shape requirements, and ensure solutions are usable, scalable, and aligned to business goals.

• Lead experimentation and continuous improvement: Run “prove, pilot, production” cycles, define success metrics, analyze performance and fan impact, and continuously refine models, prompts, workflows, and UX based on data and stakeholder feedback. Develop and lead AI first engineering processes to accelerate product, engineering, and delivery

• Evangelize and upskill the organization: Provide thought leadership on AI, share best practices, host demos and workshops, and coach teams on how to leverage agents, LLMs, vision/diffusion models, and AI workflows as force-multipliers in their day-to-day work.

Qualifications

• 8+ years of experience architecting, prototyping, and deploying robust production solutions that incorporate software engineering, infrastructure, architectural, and security best practices.

• Strong Python development skills; experience with C#, JavaScript, HTML, and CSS is beneficial.

• Hands-on experience using agentic AI software engineering solutions (e.g., Kiro, Cursor, or similar) to accelerate development and experimentation.

• 2+ years implementing AI solutions driving measurable business impact.

• Excellent working knowledge of: prompt and context engineering; AI agents, agentic architectures, tool calling, and Model Context Protocol (MCP); AI assistants, RAG, embeddings, and vector databases, evaluation, benchmarking, and guardrails.

• Experience tuning language and diffusion models, labeling and tagging data, and architecting data pipelines

• Deep understanding of architecture and design principles, and cloud services, such as: AWS, Azure, and GCP; enterprise architecture and microservices design; observability and telemetry; infrastructure as code and CI/CD pipelines.

• Experience navigating the legal, ethical, and security implications for AI, including data privacy, IP, safety, and responsible use of Generative AI.

• 4+ years experience leading cross-functional teams and collaborate effectively with global teams

• Experience approaching a problem from different angles, analyzing pros and cons of different solutions, and analytical problem-solving skills, with the ability to reframe problems, explore multiple options, and land pragmatic, high-impact solutions.

• Excellent ability to clearly communicate complex concepts simply and clearly. Weave an engaging narrative that clearly communicates complex concepts and demonstrates business impact.

• Customer- and player-centric mindset, with a passion for building solutions that empower teams and delight fans.

• Enjoy and prioritize continual learning – staying up to date with the newest AI technologies, models, tools, and solution patterns, and understanding how they can benefit EA Experiences.

• Thrive working both collaboratively and independently in a fast-paced, dynamic environment; comfortable operating in a startup-like setting within a large organization.

COMPENSATION AND BENEFITS

The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs). 

PAY RANGES

In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and equity.

In British Columbia, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.