Gcore
Tech / AI / Software
AISolutionArchitect
Neural analysis suggests this role is
optimal for mid candidates.
“AI Solution Architect at Gcore. Skills: AI Solution Architecture, GPU Cluster Design and Deployment, Infrastructure as Code, Kubernetes and Slurm Orchestration, Python/Go Programming, ML Ecosystem Understanding. Design end-to-end GPU cluster architectures (on-premises and cloud). Build and maintain Infrastructure as Code modules to automate provisioning, scaling, and monitoring of GPU resources”
Industry & Context.
Work from anywhere in the world for up to 45 days per year
What They're Looking For.
Must Have
3+ years in Cloud or GPU AI Infrastructure DevOps, Proven track record deploying GPU clusters at scale, including multi-node, multi-GPU setups, Hands-on with Ansible or similar configuration management Terraform (IaC), familiarity with Kubernetes (K8s) and Slurm, Proficient in Python / Go, Solid understanding of ML ecosystems—models, tooling, and production deployment patterns, Excellent verbal and written ability to translate complex technical concepts for diverse audiences
Nice to Have
Experience deploying high-availability inference infrastructure for production AI workloads, Implement and optimize distributed training and inference pipelines with MLflow, REST APIs, and popular frameworks (PyTorch, TensorFlow, JAX), Demonstrated ability to transition ML pipelines from proof-of-concept to robust, scalable production systems, Familiarity with GitOps workflows, Docker, Helm charts, and CI/CD for ML, Knowledge of Hugging Face transformers, Scikit-learn, and experiment tracking best practices
What You'll Do.
Design end-to-end GPU cluster architectures (on-premises and cloud)
Build and maintain Infrastructure as Code modules to automate provisioning
and monitoring of GPU resources
Host webinars and training sessions
How You'll Work.
Team & Collaboration
Collaborate with clients to design and deploy large-scale GPU clusters, containerized training pipelines, and production inference systems; Partner with Gcore's engineering and product teams to relay customer insights and drive product enhancements
Communication Scope
Translate complex technical concepts for diverse audiences; Excellent verbal and written ability
Full Job Description
The world’s digital experiences run on something invisible: the infrastructure and software that keep them fast, reliable, and secure. At Gcore, you’ll help design and deliver that foundation for an AI-driven world. We’re a global provider of infrastructure and software solutions for AI, cloud, network, and security, powering everything from real-time communication and streaming to enterprise AI and secure web applications. With 210+ edge locations, 50+ cloud regions, and thousands of GPUs , your work here can reach users and businesses across the globe. You’ll collaborate with leading technology partners such as Intel, NVIDIA, Dell, and Equinix , and work on platforms that power digital products used around the world. Our vision is simple: to connect the world to AI, anywhere, anytime. Want to work on technology that goes beyond a single product or industry? Join a global team of 550+ professionals building infrastructure and software that supports the entire digital ecosystem. As an AI Solution Architect at Gcore, you will serve as a trusted advisor to our AI-focused customers. You'll collaborate closely with clients to design and deploy large-scale GPU clusters, containerized training pipelines, and production inference systems. Your expertise in automation, infrastructure as code, and orchestration will ensure seamless, repeatable deployments across hundreds to thousands of GPUs Your Responsibilities * Architect & Deploy: Design end-to-end GPU cluster architectures (on-premises and cloud) using Ansible, Terraform, Kubernetes, and Slurm. * Customer Engagement: Lead technical deep-dives, conduct workshops, and present solutions to stakeholders at all levels. * Automation & IaC: Build and maintain Infrastructure as Code modules to automate provisioning, scaling, and monitoring of GPU resources. * Documentation & Enablement: Produce whitepapers, runbooks, and training materials; host webinars and training sessions. * Feedback Loop: Partner with Gcore's engineering a
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