Lead, AI Enablement Architect · Electronic Arts

Fri, 24 Apr 2026 13:11:07 GMT
Engineering

Electronic Arts · Singapore · hybrid

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Our EA Experiences group (XO) is dedicated to ensuring great experiences for our growing communities centered around our world-renowned brands, including fan-favourites like Apex, Battlefield, EA SPORTS FC, Madden NFL and The Sims. 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 find joy and belonging, forge friendships, and celebrate their lived experiences through the work we do every single day, together.

As the hands-on AI architect and engineer, 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.

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.

Your 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.

3+ 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, specifically AWS, Azure and GCP are beneficial

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.