Senior Infrastructure / SRE Engineer

Reliability is a feature, not an afterthought, for customers who run 24/7 mission-critical operations. At Modaxo, we're passionate about changing the face of people transportation. We believe that all transportation services should be safe, efficient, convenient, and equitable. Our products power mission-critical operations across a variety of industry sectors. We're making a strategic investment in AI to transform our solutions. As our Senior Infrastructure / SRE Engineer, you will build the foundations the whole team stands on: cloud landing zones, infrastructure-as-code, Kubernetes, CI/CD and observability. You will also establish the reliability practice that lets us ship safely. You will report to the Head of AI Platform Engineering and join a small, senior founding team building the platform from the ground up. Why This Role Is Different - Production-first. Reliability is the product for customers who rely on us 24/7. You will ship safe, repeatable delivery, not experiments. - Platform and product. You will build the foundations that the whole team and portfolio stand on. One solid platform multiplies everyone's velocity. - Domain-first, not tech-first. You will learn the domain well enough to know what "reliable" means to customers running mission-critical operations. - A founding role. As an early hire, you will establish the delivery and on-call culture and help raise the bar as we grow. - Pragmatic build or buy. You will make pragmatic build or buy decisions on infrastructure and tooling, without gold-plating. What You'll Do Foundations and Delivery - Build and own cloud landing zones, infrastructure-as-code and the Kubernetes foundations the team builds on. - Own CI/CD as a product: fast, safe, repeatable delivery. - Automate away toil, and codify operational knowledge into tooling and runbooks. Reliability and Observability - Establish observability (metrics, logs and traces), SLOs and alerting, so the platform is measurable and debuggable. - Set up and mature on-call and incident response, and drive reliability improvements from postmortems. Deployment and Cost - Support deployment into both cloud and customer-managed environments, and manage version and configuration drift. - Optimise cost and capacity, including for AI workloads. Delivering Value with Product and Customers - Work with product teams and customers to validate results and outcomes, prioritising by value. - Take a value-based development approach: prove value with the smallest useful slice, then scale what works. - Instrument and measure impact, letting evidence rather than opinion drive what ships. - Build automated QA, including tests, quality gates and regression checks, into the delivery pipeline. Building the Team and Ways of Working - Help build the team by establishing on-call and reliability culture, and mentor as we grow. - Foster a culture of technical excellence, customer obsession and pragmatic shipping. - Partner with product teams across the portfolio who own their own roadmaps. What You'll Bring We look at demonstrated experience and scope, not years served, and we don't expect every candidate to tick every box. - Production infrastructure: You have built and run production cloud infrastructure and owned its reliability. - Operations as engineering: You treat operations as engineering, not ticket-driven ops. - On-call maturity: You have carried real on-call for what you built. - Clear communication: You explain your thinking clearly to engineers, product partners and customers, and bring people along. - Value and pragmatism: You focus on outcomes and value, and make pragmatic calls to ship. Bonus Points Any of these strengthen an application; none are required. - Kubernetes and IaC: Kubernetes and infrastructure-as-code in production. - Azure depth: Landing zones, networking and identity on Azure. - Customer-managed environments: Shipping software into environments the vendor does not fully control. - Regulated delivery: Delivery into regulated or restricted environments. - Compute cost: Cost optimisation for GPUs or other expensive compute. - Languages: Comfortable in Python, C#/.NET or Go for tooling and automation. - Architecture: System and platform design, and trade-off judgement such as one-way versus two-way doors. - Enterprise scale: Experience building or operating enterprise-scale software, and its reliability, security and integration demands. - AI-assisted engineering: You use AI coding assistants productively and supervise their output with judgement. New to some of this? If you bring the essentials above and are excited by the problem, we'd still like to hear from you.