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.
You will be the hands-on lead architect for our AI platform and the AWS infrastructure that powers it, reporting to the Director, Agentic Solutions. You will design, build, and operate the cloud foundation our production AI agents run on, going deep in AWS and Amazon Bedrock to make agents reliable, secure, and cost-effective at scale. You’ll architect and ship the model gateways, agent runtime and orchestration, eval and observability frameworks, vector stores, and RAG services that the rest of XO builds on, and you’ll still build agents end to end when the work calls for it. 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 product, data, security, IT, and engineering teams. You will create scalable AI pipelines and workflows that let teams 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
Own the platform foundation: design and run the cloud infrastructure our AI agents and solutions depend on, spanning account and network architecture, IAM, deployment patterns, observability, security, scaling, and cost.
Go deep on the agent runtime: own model access and routing, agent orchestration, knowledge bases, and guardrails, and make the calls on when to use hosted models versus self-managed serving.
Build and operate the platform services: stand up the compute, eventing, data stores, vector databases, and integration layer that connect agents to internal systems and EA Experiences workflows.
Build production AI agents end to end: agent architectures, tool calling, MCP integrations, multi-agent orchestration, memory, evaluation, and guardrails, building alongside the team when the work calls for it.
Standardize infrastructure as code and CI/CD: create reusable infrastructure-as-code modules and automated pipelines so the platform is repeatable and safe to change.
Productionize and operate at scale: own the path from prototype to production, including integration with existing platforms and services, SLOs, reliability, cost controls, and incident response for AI workloads.
Embed guardrails, safety, and FinOps: implement policies and evaluation frameworks for IP, privacy, and security, and define eval gates and cost and latency budgets that ship with every AI system.
Partner across EA: work directly with teams to understand their processes and opportunities, then rapidly prototype, iterate, and productionize AI solutions that drive efficiency, expansion, and transformation.
Evangelize and upskill teams: share best practices, host demos and workshops, and show teams how a solid platform and well-built agents expand what’s possible in their work.
Your Qualifications
7+ years designing, building, and deploying production-grade software and the cloud infrastructure behind it, with strong software engineering, security, and infrastructure best practices.
Deep, hands-on AWS experience is the core of this role, including Amazon Bedrock and related AI/ML services (model access, AgentCore, Knowledge Bases, Guardrails), IAM, networking (VPC), compute and serverless (Lambda, ECS/Fargate, containers), observability and telemetry (CloudWatch, tracing, structured logging), and secrets management.
Strong infrastructure-as-code and CI/CD experience (CDK, Terraform, or CloudFormation), with a track record of building for reliability, scale, and cost efficiency.
Strong Python development skills; working knowledge of at least one additional backend language (JavaScript/TypeScript and Node.js, Go, Java, or C#).
Hands-on experience building production AI agents, not just prototypes, including prompt and context engineering; agentic architectures, tool calling, and Model Context Protocol (MCP); RAG, embeddings, and vector databases; and model evaluation, benchmarking, and guardrails.
Experience building the integration layer behind AI products: APIs, auth, eventing, and data pipelines, and integrating AI into existing platforms and services.
Enterprise architecture and microservices design; event-driven and async messaging patterns; API gateways and contracts.
Extensive experience with spec-driven development and agentic AI coding tools such as Claude Code, Cursor, or Kiro.
Experience navigating the legal, ethical, and security implications of AI, including data privacy, IP, and safety, and translating policy into engineering controls.
Thrive working both collaboratively and independently, with excellent creative, critical thinking, and problem-solving skills, and a demonstrated ability to clearly articulate complex technical concepts.
Experience working in a marketing organization or a gaming company is beneficial.
About Electronic Arts
We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.
Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.
