Electronic Arts

Contract: Permanent.

Location: Madrid (relocation support can be provided).

Work Model: Hybrid (3 days a week onsite).

Join us in building and enhancing AI-powered developer tools that transform how our engineers create games like FC, Apex Legends, Madden, Battlefield, NHL, and skate. You will collaborate with teams across EA, leveraging Generative AI, LLMs, and advanced software engineering to reimagine how we write, test, and maintain code. Working onsite at our new EA Madrid office and reporting to a Senior Engineering Manager, you will:

• Provide technical leadership in architecting and building AI-driven enterprise solutions that enhance developer productivity. You will help shape how our engineers interact with Generative AI.

• Apply strong communication and collaboration skills to work effectively with our internal community, external vendors, and our team’s Center of Excellence, ensuring alignment on strategy and adoption of AI solutions.

• Collaborate with product, research, and engineering teams across EA to define product vision, roadmap, and strategy for AI-powered tools, and present to senior leadership.

• Evaluate LLM models, APIs, and open-source frameworks alongside traditional build-vs-buy options.

• Mentor engineers across the company in Generative AI integration, prompt engineering, and evaluation best practices, shaping the next generation of EA developers.

• Ensure systems are reliable, secure, and scalable, balancing experimentation with production-grade rigor.

• Support internal users by delivering solutions that make AI a natural extension of their development workflows. 

Qualifications

• 8+ years developing enterprise-level solutions, with recent focus on integrating AI into those solutions.

• Hands-on experience integrating Generative AI/LLMs (OpenAI, Anthropic, Mistral, or open-source) into production workflows.

• Strong programming skills in Python or C#, with exposure to modern web frameworks.

• 5+ years with cloud platforms (Azure/AWS preferred), microservices, and distributed systems.

• Experience with prompt optimization, embeddings, vector databases, and RAG pipelines.

• Familiarity with DevOps practices, CI/CD, and observability in AI systems.

• Proven ability to drive projects across cross-functional teams with clear technical vision.      

Nice To Have

• Experience building developer tools, IDE extensions, or AI productivity platforms.

• Experience with building Grafana dashboards and PowerBI reports.

• Knowledge of fine-tuning and evaluation methodologies.

• Familiarity with Docker, Kubernetes, Terraform, or cloud-native MLOps frameworks.

• Contributions to open-source AI or developer productivity projects.

• Cloud certifications in Azure or AWS.