Director, AI Network & Data Center Engineering

CVS Health

Santa Fe (NM)

On-site

USD 144,000 - 288,000

Full time

3 days ago

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Benefits offered by this job

Comprehensive benefits package

Job summary

CVS Health is seeking a Lead Director of AI Network & Data Center Engineering to shape the strategy, design, and delivery of the company’s network infrastructure for enterprise applications and AI workloads.

You will lead a high‑performing team, partner with cloud, platform, and cybersecurity leadership, and drive automation, IaC, and performance optimization to support long‑term growth and digital transformation.

Qualifications

10+ years' experience in network and/or data center engineering.
5+ years' experience in a strategic leadership position with people management.
5+ years' experience in large scale enterprise environments.

Responsibilities

Define and enforce network architecture standards, security controls, and compliance policies.
Establish best practices for configuration, deployment, and operations.
Ensure alignment with enterprise governance frameworks (HIPAA, NIST, PCI, HITRUST, CSA).
Advise executives on network strategy, roadmaps, emerging technologies, and industry trends.
Partner with cross‑functional teams to deliver integrated, secure and scalable solutions.
Engage vendors on solution architectures, design, contracts, and delivery.
Design and implement data center fabrics (leaf‑spine, Clos, EVPN/VXLAN).
Design AI/GPU‑optimized networking and related technologies.
Optimize performance for GPU workloads (RDMA, RoCE, ECN, PFC).
GCP and multi‑cloud network architectures.
Routing & switching (BGP, OSPF, MPLS, STP; Cisco, Juniper, Arista).
High‑speed networking (100/200/400Gb+)
GPU cluster networking, traffic optimization, and congestion management
Drive network monitoring and performance optimization (SolarWinds, NetFlow, Wireshark)
Support SaaS and multi‑tenant environments with zero trust patterns
Oversee 24/7 network operations across cloud and data centers
Lead incident response and ensure high availability, resiliency and scalability across network and cloud environments
Build and mentor high‑performing engineering teams
Foster a culture of collaboration, accountability, and continuous learning
Advance networking capabilities for AI/ML infrastructure and GPU clusters
Champion automation and Infrastructure as Code (IaC)
Contribute to industry and open‑source initiatives
Own network architecture strategy and roadmap
Define standards for AI, cloud, and data center environments
Support budgeting, risk management, and long‑term planning