Principal Founding Engineer, AI-Native Product Incubation

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.

The future of entertainment is interactive, and our Ventures Group plays an important role in this future by building content, culture, and community that take us Beyond Gaming. Our focus is how fans experience sport in their everyday lives, before, during, and after the live moment. We build consumer experiences such as mobile apps, web, and companion products, and the platform capabilities behind them, such as social, predictions, and live content, that new products and existing EA games can share.

Small, AI-assisted teams take ideas from first prototype through closed beta to wide release, shipping working product every week and letting evidence decide what scales. We are seeking an experienced Founding Engineer to own the technology behind these products as they go from 0 → 1 and beyond. This is a hands-on, full-stack role with a strong lean towards scalable backend systems: you will architect products end to end, from backend services, event streaming, and durable workflows through to web and native iOS and Android clients, working closely with our client leads.

You will build in an AI-native way, with coding agents central to how you design, ship, and operate software.

Key Responsibilities

Help own the technical architecture and direction of Ventures products end to end, across backend services, cloud infrastructure, and web and native iOS and Android clients. Take new ideas from 0 → 1: build testable versions quickly to generate evidence, then harden what works for growth. Design, build, and operate scalable backend systems, including gRPC services, event streaming, and durable workflows that serve real-time experiences around live sport.

Build platform capabilities, such as social, predictions, and live content, that several products and existing EA games can share. Architect for scale and failure: fan-out cost, backpressure, idempotency, reconnect behaviour, data growth, and recovery as audiences grow. Design features end to end across service and client boundaries, including API and data contracts, real-time delivery, and local-first sync on mobile, partnering with the client leads on web, iOS, and Android implementation.

Build with AI coding agents as a core part of your workflow, and own the tooling, guardrails, and review practices that let agents work safely and quickly across the codebase. Own production, including environments, deployments, infrastructure as code, observability, incident response, and the cost of cloud and third-party services.

Release user-facing changes safely through feature flags, staged rollouts, and tested rollback plans, holding every launch to EA's bar for load, security, localisation, and monitoring. Integrate with EA platform services such as identity, moderation, and security, and with third-party sports data and AI providers. Set the engineering standard for code review, testing, documentation, and architectural decisions, keeping fast-moving codebases maintainable.

Partner with product and design to shape roadmaps, turning ideas into technical plans with clear trade-offs. Support and onboard new engineers joining the team, and share architecture patterns and AI-native practices across Ventures so each new product starts on proven foundations. How Your Success Will Be Measured: Speed from idea to a testable product, with each release producing the evidence the next decision needs.

Reliability, performance, and scalability of our products in production, especially at live-match peaks. Delivery of high-quality features across backend and clients, aligned with product goals and technical requirements. Quality of architectural decisions, and the maintainability and extensibility of the systems you own.

Safe, observable releases: controlled rollouts, measurable outcomes, and fast recovery when something goes wrong. Effective use of AI coding agents to increase delivery speed without lowering the quality bar. A clear technical direction that client leads, product, and partner teams can plan around. Cost-efficient operation of cloud infrastructure and third-party services as usage grows.

What You Bring: 10+ years of professional software engineering experience, including taking consumer products from 0 → 1 and operating them in production. Deep backend expertise designing, building, and operating scalable distributed systems, ideally in Go with gRPC and Protocol Buffers. Experience with event-driven and real-time architectures, ideally including message streaming such as NATS Jet.

Stream or Kafka, and durable workflow engines such as Temporal. Strong data modelling across relational, document, and in-memory stores, ideally PostgreSQL, Firestore, and Redis. Experience running production services in the cloud, ideally Google Cloud and Kubernetes (GKE), with infrastructure as code such as Pulumi or Terraform, CI/CD, and observability through Open.

Telemetry or similar. Experience building software with AI coding agents, or a strong, demonstrable interest in doing so. This is essential for the role. Enough web and mobile fluency to architect features end to end and review client designs, ideally with SwiftUI on iOS, Kotlin with Jetpack Compose on Android and React on Web.

Proven ability to own a system end to end and make sound technical decisions independently. Experience shipping user-facing changes safely with feature flags, staged rollouts, and production monitoring. Experience building real-time, social, sports, gaming, or entertainment products, or as a founding engineer, is a strong plus.

Experience building LLM-powered or agentic product features is a plus. Soft Skills & Values: Takes ownership of outcomes, not just tasks. Pragmatic judgement about speed, quality, and scale, with strong attention to detail. Comfortable with ambiguity, and ready to change course when the evidence says so. Clear communicator who can explain technical trade-offs to engineers, product, and leadership.

Collaborative partner to client leads, product, design, and partner teams. Generous with knowledge, and effective at bringing new engineers up to speed. Curious about how AI is changing software development, and keen to help shape it. Commitment to inclusivity, trust, and continuous improvement.