Senior Infrastructure / SRE Engineer

The Role 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. You will build the foundations the whole team stands on - cloud landing zones, infrastructure-as-code, Kubernetes, CI/CD, and observability - and establish the reliability practice that lets us ship safely. Our customers run 24/7 mission-critical operations, so reliability is a feature, not an afterthought. You'll report to the Head of AI Platform Engineering and join a small, senior founding team building the platform from the ground up. The opportunity: set up the delivery and reliability backbone of a new platform, and own it as a product. Why this role is different - It's production-first. Reliability is the product for 24/7 customers - you'll ship safe, repeatable delivery, not experiments. - It's platform AND product. You build foundations the whole team and portfolio stand on - one solid platform multiplies everyone's velocity. - It's domain-first, not tech-first. You'll learn the domain enough to know what 'reliable' means to customers running mission-critical operations. - It's a founding role - you help build the team. As an early hire you'll establish the delivery and on-call culture and help raise the bar as we grow. - It's pragmatic build/buy. You'll make pragmatic build/buy decisions on infrastructure and tooling, not gold-plate. What You'll Do Foundations & 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; codify operational knowledge into tooling and runbooks. Reliability & Observability - Establish observability (metrics, logs, traces), SLOs, and alerting so the platform is measurable and debuggable. - Set up and manage on-call and incident response; drive reliability improvements from postmortems. Deployment & Cost - Support deployment into both cloud and customer-managed environments, and manage version and configuration drift. - Optimize cost and capacity, including for AI workloads. Delivering Value with Product & Customers - Work with product teams and customers to validate results and outcomes, prioritizing by value. - Take a value-based development approach: prove value with the smallest useful slice, then scale what works. - Instrument and measure impact; let evidence - not opinion - drive what ships. - Build automated QA - tests, quality gates, and regression checks - into the delivery pipeline. Building the Team & Ways of Working - Help build the team: establish 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've 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've 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 + 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 doesn't fully control. - Regulated delivery: Delivery into regulated or restricted environments. - Compute cost: Cost optimization for GPUs or other expensive compute. - Languages: Comfortable in Python, C#/.NET, or Go for tooling and automation. - Architecture experience: System/platform design and trade-off judgement - one-way vs 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.