Principal Founding Engineer, AI-Native Product Incubation

This role will own the technology behind Ventures products as they go from 0 → 1 and beyond. It is a hands-on, full-stack position with a strong lean towards scalable backend systems, architecting products end to end from backend services, event streaming, and durable workflows through to web and native iOS and Android clients. The role works closely with client leads and builds in an AI-native way, with coding agents central to how software is designed, shipped, and operated.

• 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, and take new ideas from 0 → 1 by building testable versions quickly to generate evidence before hardening 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, and build platform capabilities such as social, predictions
• And live content that multiple products and existing EA games can share.
• Architect for scale and failure, covering 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 client leads on web, iOS, and Android implementation.
• Build with AI coding agents as a core part of the 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, and support and onboard new engineers while sharing architecture patterns and AI-native practices across Ventures.
• Partner with product and design to shape roadmaps, turning ideas into technical plans with clear trade-offs.

• 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.
• Experience with event-driven and real-time architectures.
• Strong data modelling across relational, document, and in-memory stores.
• Experience running production services in the cloud with infrastructure as code, CI/CD, and observability.
• 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.
• 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.
• 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.

• Go with gRPC and Protocol Buffers for scalable distributed systems.
• Message streaming such as NATS JetStream or Kafka, and durable workflow engines such as Temporal.
• PostgreSQL, Firestore, and Redis for data modelling.
• Google Cloud and Kubernetes (GKE), with infrastructure as code such as Pulumi or Terraform, and observability through OpenTelemetry or similar.
• SwiftUI on iOS, Kotlin with Jetpack Compose on Android, and React on Web for web and mobile fluency.
• Experience building real-time, social, sports, gaming, or entertainment products, or as a founding engineer.
• Experience building LLM-powered or agentic product features.