Note: The job is a remote job and is open to candidates in USA. Enterone is a Cisco-focused technology solutions company accelerating its AI infrastructure practice. The Senior AI Infrastructure Engineer will advise clients on AI-ready infrastructure, design and secure scalable environments, and lead implementations from proof-of-concept through production. The role also includes automation, technical enablement, collaboration with Cisco teams, and mentoring junior engineers.
Responsibilities
- Design and advise on scalable AI/ML infrastructure using Cisco UCS, HyperFlex, and Intersight — including GPU cluster configurations for training and inference
- Advise clients on AI roadmaps and evaluate emerging Cisco AI platform capabilities to shape solution offerings
- Architect low-latency network fabrics (Cisco ACI, Catalyst, Nexus) with segmentation, QoS, and SD-WAN for distributed AI workloads; embed zero-trust security to protect AI models, data pipelines, and comply with regulated environment requirements
- Lead end-to-end deployments of AI infrastructure solutions — from rack-and-stack through software configuration and handoff
- Automate provisioning and lifecycle management using Cisco Intersight, Ansible, Terraform, and Python; establish monitoring and performance benchmarking for AI workloads
- Develop playbooks and reference architectures; deliver technical workshops to client stakeholders from engineers to C-suite
- Collaborate with Cisco teams on roadmap developments; mentor junior engineers and grow Enterone's AI practice
Skills
- • 5+ years of hands-on experience in infrastructure engineering, with at least 2 years focused on AI/ML infrastructure
- • Deep expertise with Cisco UCS, HyperFlex, ACI, Catalyst, Nexus, and Meraki; proficiency in BGP, OSPF, VXLAN, and network automation
- • Familiarity with AI/ML frameworks (PyTorch, TensorFlow) and the infrastructure demands of GPU scheduling, distributed training, and high-bandwidth storage
- • Proficiency in infrastructure-as-code (Ansible, Terraform, Intersight workflows) and scripting in Python or Bash
- • Excellent written and verbal communication skills — ability to present complex architecture to both technical and non-technical audiences
- • Cisco certifications: CCNP Data Center, CCIE Data Center, or Cisco Certified DevNet Professional
- • Experience with Cisco AI/ML products (Intersight Workload Optimizer, Nexus AI); MLOps platforms (Kubeflow, MLflow) and containerized AI on Kubernetes
- • Background in managed services or consulting; familiarity with hybrid cloud (AWS/Azure/GCP) and high-performance storage for AI
Benefits
- A pivotal role in building Enterone's AI infrastructure practice from the ground up.
- Bonus
- Comprehensive benefits
- An annual certification and training budget
- Flexible, remote-friendly work environment
- A high-trust culture
Company Overview
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