AI Architect

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.