Enterprise Architect (Professional Services). Remote in Europe.
Remote
Job Summary
Partner with enterprise customers to understand their business strategy and translate it into technology direction, assessing current-state landscapes to design coherent target-state architectures. Develop transformation roadmaps that sequence decisions to balance business value, risk, cost, and operational reality while establishing architecture principles and standards. Evaluate trade-offs across cloud, container, infrastructure, and AI options to make defensible recommendations, acting as a trusted advisor between stakeholders and delivery teams. Present architectures and rationale to executives and engineers, engaging on-site across regions for discovery and advisory. Requires 10+ years in infrastructure or platform engineering with fluency in Kubernetes, OpenStack, and AI governance, with willingness to travel primarily within the EU and US.
Required Qualifications
- 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.
- Bachelor's degree in Computer Science or a related field, or equivalent experience.
- 10+ years across infrastructure or platform engineering, including customer-facing architecture or advisory experience
Desired Qualifications
- experience with Mirantis Openstack for Kubernetes (MOSK)
- 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).
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