AI Platform Engineer

• 4+ years of software engineering experience building full-stack or backend-heavy product systems.
• 3+ years of meaningful cloud infrastructure experience, including hands-on work with Kubernetes, infrastructure-as-code, and networking.
• Credible, practical experience leveraging AI tools - including agents, SDKs, and coding assistants - to augment developer productivity and ship software more effectively.
• Strong fundamentals in distributed systems, API design, security, and operational excellence.
• A bias towards simplicity, paved paths, and building infrastructure that others can safely build on.

• Experience with one or more of Python, TypeScript, Go, or Rust.
• Experience building developer platforms, internal tooling, or platform-as-a-product.
• Familiarity with the Model Context Protocol (MCP), agent orchestration, RAG, or context engineering.
• Experience designing data-access, identity, or governance layers for AI/agentic systems.
• Experience operating in a regulated environment.

We are on a mission to pioneer the world's next era of play. As we grow across Europe and Latin America, we're building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.

You will be joining the Core AI tribe within Super's Platform organisation, a team responsible for building the general-purpose infrastructure that enables product and engineering teams to leverage AI capabilities with greater effectiveness. As an AI Platform Engineer, you will design and build the core infrastructure and developer-facing tooling that powers AI and agent development across Super. The infrastructure you build will be used by every engineering and product team, making this one of the most impactful platform roles in the organisation. We are currently growing the team and hiring multiple engineers at the senior and staff track level.

• Design, build, and operate general-purpose AI platform infrastructure - including MCP gateways, the internal agentic platform, context engineering services, and supporting SDKs and tooling.
• Build secure, governed data-access and identity layers that serve both human users and autonomous agents, with appropriate access controls, auditing, and observability.
• Develop developer-facing tooling and paved paths that make it straightforward for product and engineering teams to build, deploy, and observe AI-powered and agentic workflows.
• Own services end to end: from architecture and implementation through to deployment, monitoring, and on-call operation on a Kubernetes-based cloud platform.
• Define and codify infrastructure using infrastructure-as-code; improve the reliability, networking, and performance of the platform.
• Partner with product, security, and infrastructure teams to ensure platform capabilities are safe, compliant, and production-ready.
• Set engineering standards and mentor others; act as a force multiplier for how AI is adopted across the organisation.