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Executive Director, AI Infrastructure & Platform Engineering

Job in Bangor, Penobscot County, Maine, 04401, USA
Listing for: Koitecc Solutions
Full Time position
Listed on 2026-07-25
Job specializations:
  • IT/Tech
    Systems Engineer, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 175100 - 334750 USD Yearly USD 175100.00 334750.00 YEAR
Job Description & How to Apply Below

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 Fin Ops.
  • 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 Open Shift 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 Fin Ops governance - utilization optimization, tenant quota enforcement, and cost reduction - in partnership with the Finance organization.
Security and Compliance
  • Empower the Security SRE Lead to…
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