Lead Platform Architect
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Key skills for this role
About the Role
Electronic Arts is looking for a hands-on Lead Platform Architect to design, build, and operate the cloud foundation for production AI agents. You will own the AI platform infrastructure on AWS, including model gateways, agent runtime, observability, and RAG services.
Key Skills for This Role
Responsibilities
- Own the platform foundation: design and run the cloud infrastructure our AI agents and solutions depend on.
- Go deep on the agent runtime: own model access and routing, agent orchestration, knowledge bases, and guardrails.
- Build and operate the platform services: compute, eventing, data stores, vector databases, and integration layer.
- Build production AI agents end to end: agent architectures, tool calling, MCP integrations, multi agent orchestration, memory, evaluation, and guardrails.
- Standardize infrastructure as code and CI/CD: create reusable modules and automated pipelines.
- Productionize and operate at scale: own the path from prototype to production, including SLOs, reliability, cost controls, and incident response.
- Embed guardrails, safety, and FinOps: implement policies and evaluation frameworks for IP, privacy, and security.
- Partner across EA: work directly with teams to understand processes and opportunities, then rapidly prototype and productionize AI solutions.
- Evangelize and upskill teams: share best practices, host demos and workshops.
Requirements
- 7+ years designing, building, and deploying production grade software and the cloud infrastructure behind it.
- Deep, hands on AWS experience including Amazon Bedrock and related AI/ML services, IAM, networking (VPC), compute and serverless, observability, and secrets management.
- Strong infrastructure as code and CI/CD experience (CDK, Terraform, or CloudFormation).
- Strong Python development skills; working knowledge of at least one additional backend language (JavaScript/TypeScript, Go, Java, or C#).
- Hands on experience building production AI agents, including prompt engineering, agentic architectures, tool calling, MCP, RAG, embeddings, vector databases, and model evaluation.
- Experience building the integration layer behind AI products: APIs, auth, eventing, and data pipelines.
- 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.
Full Job Posting
Description & Requirements
- 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.
- 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.
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, struc
- 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.
- Experience working in a marketing organization or a gaming company is beneficial.
Pay Transparency – North America
- British Columbia (depending on location e.g. Vancouver vs. Victoria): CAD 122,300 CAD 170,700 CAD.
- Washington (depending on location e.g. Seattle vs. Spokane): CAD 133,100 CAD 178,400 USD.
- Pay is just one part of the overall compensation at EA.
- In the US, benefits include paid time off, sick time, holidays, parental leave, medical/dental/vision insurance, life insurance, disability insurance, and 401(k).
- For Canada, benefits include vacation, sick time, parental leave top up, extended health/dental/vision coverage, life insurance, disability insurance, and retirement plan.
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