Executive Director, AI Infrastructure & Platform Engineering

at CVS Health in Work At Home, United States

Job Description

We’re building a world of health around every individual – shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

Job Description

The Executive Director, AI Infrastructure & Platform Engineering is a senior engineering leadership role responsible for standing up, operating, and continuously improving CVS Health’s on-premises AI compute platform. This position owns the physical and platform layers of CVS’s Enterprise AI Factory – a frontier-class GPU compute environment running NVIDIA Blackwell systems across a high-throughput RoCE v2 fabric, hosted in co-located data center facilities, with multi-site expansion underway.

Reporting to the Global Head of Infrastructure/AI Operations and Service Delivery, this leader will establish operational baselines across the full infrastructure stack – hardware, network fabric, GPU clusters, storage, and the operating systems and orchestration layers above – and build the Site Reliability Engineering practice that delivers the availability, reliability, and performance that frontier AI workloads demand.

This is a greenfield organizational build. The Executive Director will define the operating model, set the engineering standards, hire and develop the team, and establish the long-term operations capability that will govern CVS’s AI infrastructure for years ahead.

Key Responsibilities

Strategy and Leadership:

+ Define and execute the long-range vision and strategy for AI infrastructure and platform engineering, with availability (>99.99%), reliability, and platform performance as the primary measures of success.

+ Recruit, hire, develop, and retain a high-performing engineering organization spanning infrastructure, network, platform reliability, observability, security, 24/7 operations, change and release management, and FinOps.

+ Establish clear ownership, accountability, and performance expectations across all functional teams; foster a culture of operational excellence, engineering rigor, and continuous improvement.

+ Provide executive-level communication to senior leadership on platform status, milestones, risk posture, and strategic initiatives.

Infrastructure and Platform Engineering:

+ Own the physical layer of the AI compute environment – GPU compute, storage, network fabric, capacity planning, and hardware lifecycle accountability.

+ Direct bare-metal Kubernetes and OpenShift operations, including cluster administration, GPU quota governance, infrastructure-as-code adoption, and availability baseline enforcement.

+ Govern high-performance network fabric operations – RoCE v2, spine-leaf topology, lossless Ethernet tuning, congestion management, and segmentation.

+ Establish and enforce operational baselines across every layer of the stack – hardware, fabric, platform, and workload – with deviations detected, escalated, and resolved within defined SLAs.

+ Direct Innovation POD strategy to develop self-healing and autonomous capabilities that proactively prevent service degradation before it impacts availability.

Operations and Reliability:

+ Build and sustain a high-performing 24/7 operations model – designed for sustainable, predictable coverage with no mandatory overtime and measurable team health and retention.

+ Drive end-to-end observability across the physical and platform layers, with continuous feedback loops connecting monitoring data to incident response, change decisions, and improvement cycles.

+ Oversee change management so every modification is risk-assessed, monitored during rollout, and baseline-validated post-deployment.

+ Ensure configuration consistency and drift detection across all platform components to prevent baseline degradation over time.

+ Lead GPU FinOps governance – utilization optimization, tenant quota enforcement, and cost reduction – in partnership with the Finance organization.

Security and Compliance:

+ Empower the Security SRE Lead to maintain a world-class security posture across the infrastructure and platform layers, with robust compliance to frameworks including HIPAA and NIST AI RMF.

+ Govern access controls, audit logging, vulnerability management, and network segmentation across the AI compute environment.

Program Transition and Operating Model:

+ Lead the operational transition from program-launch staffing to permanent CVS-owned operations – governing phased handoffs, competency validation, and milestone sign-offs to ensure minimal disruption to platform availability and business operations.

+ Establish and lead the long-term operating model by institutionalizing key technical, architectural, and delivery leadership capabilities into permanent CVS roles, ensuring the organization is fully self-sustaining at program close.

Vendor and Stakeholder Management:

+ Own vendor relationships, contract performance, and accountability across the hardware, networking, platform, and managed-services stack.

+ Manage budget ownership for the AI infrastructure and platform engineering organization, including capital planning and operational expense governance.

Required Qualifications

The successful candidate will demonstrate technical depth, executive presence, and a proven record of operating physical infrastructure at data center scale. The ideal candidate will bring the following experience, knowledge, and abilities:

+ 10+ years of engineering leadership experience, with substantial time directly owning physical infrastructure at data center scale – including hardware lifecycle, capacity planning, and facility coordination (power, cooling, rack-and-stack execution).

+ Hands-on production ownership of bare-metal Kubernetes or OpenShift. Managed cloud services (EKS, GKE, AKS) alone do not substitute for the practitioner expertise this role requires.

+ Fluency with high-speed cluster fabrics – RoCE v2, InfiniBand, EVPN-VXLAN, or carrier-grade equivalent – and the operational discipline these fabrics require (PFC, ECN, lossless tuning, congestion management).

+ 5+ years leading multiple technical teams simultaneously, including 24/7 operations organizations, with measurable team health, retention, and performance outcomes.

+ Proven success establishing and enforcing operational baselines, SLO / SLI / error-budget frameworks, and observability-driven continuous improvement in physical-infrastructure-anchored environments.

+ Hardware lifecycle, vendor accountability, and facility coordination experience – including capacity planning, RMA management, and multi-vendor escalation.

+ Experience leading operational transitions or organizational build-outs at scale, with business continuity and minimal disruption as non-negotiables.

+ Executive-level stakeholder communication, vendor negotiation, and budget ownership.

Preferred Qualifications

+ Hands-on experience with Cisco UCS, NVIDIA HGX / DGX / Blackwell systems, and VAST or comparable distributed NVMe storage.

+ Direct experience operating GPU clusters of 32 or more GPUs in production environments – including HPC, AI training, research computing, or comparable workloads.

+ NVIDIA AI Enterprise, NVIDIA Run:AI, NVIDIA Base Command Manager, or comparable GPU orchestration platform experience.

+ Healthcare or other regulated-industry background (HIPAA, NIST AI RMF, SOX, FedRAMP, ITAR).

+ Chaos engineering and AI-driven operations experience – predictive alerting and automated remediation patterns.

+ Background in innovation programs, POD structures, or centers of excellence.

Education

+ Required: Bachelor’s