Enterprise Architect (Professional Services)

Mirantis provides enterprises with the fastest path to a modern cloud built for AI. We deliver a full infrastructure foundation for VMs, containers, and orchestration through a distinctive model that enables organizations to run their platforms at scale across public cloud, private cloud, and the edge. Our innovative AI solutions for the enterprise bring AI inference and governance into their own environments, giving businesses control over the models and data that power their applications. Mirantis serves many of the world's leading enterprises, including Adobe, DocuSign, Liberty Mutual, PayPal, Reliance Jio, Splunk, STC, Vodafone, and Volkswagen. Learn more at www.mirantis.com. Job Summary We are seeking an Enterprise Architect whose focus is on the whole: someone who aligns the technology landscape of enterprise customers with their business objectives. You will work with client leadership and technical teams to understand where a business is trying to go, assess the current-state landscape, and shape a coherent target-state architecture and roadmap that moves technology decisions in service of business outcomes. This is a role about synthesis and judgment. You are well versed across a broad range of technologies - cloud, containers, operating systems, platform components, and AI - but your value is in seeing how they fit together into a system that serves the enterprise, weighing trade-offs across cost, risk, operational fit, and time-to-value, and communicating those choices clearly to both executives and engineers. What matters most is the ability to think holistically about business-technology alignment and to reason credibly across the technology domains below. Key Responsibilities • Partner with enterprise customers to understand their business strategy, drivers, and constraints, and translate them into technology direction. • Assess current-state technology landscapes and design coherent target-state architectures that serve business objectives rather than optimizing individual components in isolation. • Develop transformation roadmaps, sequencing decisions to balance business value, risk, cost, and operational reality. • Establish architecture principles, standards, and reference models that give the enterprise a consistent frame for decision-making. • Evaluate trade-offs across cloud, container, infrastructure, and AI options and make clear, defensible recommendations on where each fits within the broader landscape. • Become a trusted advisor and translator between business stakeholders and technical delivery teams. • Present architectures, roadmaps, and rationale to audiences ranging from customer executives to hands-on engineers. • Engage on-site with customers across regions as part of the discovery, design, and advisory process. Required Skills/Abilities: • A demonstrated ability to think about the enterprise as a whole - connecting technology decisions to business goals - rather than working only at the level of individual systems. • Broad, credible fluency across a range of technologies, including: • Private cloud platforms including OpenStack; experience with Mirantis Openstack for Kubernetes (MOSK) is preferred. • Kubernetes-based container platforms including Mirantis k0s and Mirantis Kubernetes Engine (MKE) • Multi-cluster management tools such as Mirantis k0rdent • Workload orchestration - how modern platforms schedule, route, and manage workloads across clusters and environments. • VMware estate modernization - enough understanding of vSphere/VMware environments to advise enterprises on virtualization strategy and migration paths as they modernize toward open platforms. • Bare-metal provisioning and physical infrastructure lifecycle. • Automation (e.g., Ansible, Terraform, or equivalent infrastructure-as-code and configuration-management approaches). • The components of a cloud or container platform and how they fit together. • Enterprise AI infrastructure - enough understanding of how AI inference is deployed and governed in the enterprise (model serving, inference stacks, and the associated data, security, and governance implications) to reason about where it fits and its trade-offs. Deep ML specialization is not required; the focus is the infrastructure and governance layer, not model development. • Strong ability to communicate architecture and rationale to both business and technical audiences. • Ability and willingness to travel, primarily within the EU and US. Nice to have • Familiarity with Software-Defined Networking (SDN) as part of a broader architecture picture. • Familiarity with Software-Defined Storage (SDS) as part of a broader architecture picture. • Experience with enterprise architecture frameworks or methods (e.g., TOGAF or equivalent). • Exposure to hybrid or multi-cloud strategy and workload portability. • Additional European language skills (beyond the required English). • Relevant industry certifications (cloud, container). ...