Principal Product Manager - Hardware Accelerator Virtualization

Red Hat•Boston, MA

4d•Hybrid

About The Position

Manage end-to-end execution of hardware accelerator virtualization projects on Red Hat OpenStack and OpenShift, ensuring GPU enablement, resource scheduling, and delivery of Compute/Cyborg components stay within scope, schedule, and allocated budget. Confer with engineering, quality, and hardware partner teams to identify and resolve technical blockers in kernel‑level driver alignment, secure boot compliance, and upgrade compatibility across OpenShift hardware enablement components (KMM, NFD, DTK).

Requirements

Master’s degree (U.S. or foreign equivalent) in Mechanical Engineering, Technology Management, Business Administration or related field and five (5) years of experience in the job offered or related role OR Bachelor's degree (U.S. or foreign equivalent) in Mechanical Engineering, Technology Management, Business Administration or related field and seven (7) years of experience in the job offered or related role.
Must have three (3) years of experience with: hardware accelerators, including GPUs and FPGAs, and their application in AI/ML workloads; AI/ML technologies and frameworks, including classifiers, PyTorch, Tensorflow, and LLMs; and defining virtualization architecture requirements across OpenStack Nova, KVM/libvirt, and Kubernetes layers to support GPU passthrough, partitioning, and performance tuning.
Must have three (3) years of experience as a technical product manager driving enterprise software solutions, including cloud infrastructure or virtualization platforms.
Must have two (2) years of experience with: Red Hat OpenShift Platform, Red Hat OpenStack Platform, VMware vSphere, or other enterprise-level infrastructure solutions; the Agile development process; overseeing the integration and lifecycle management of hardware enablement components at the kernel-level, driver compatibility, and upgrades; and management frameworks for various types of accelerators.

Responsibilities

Monitor and track milestones for AI/ML workload optimization on virtualized environments, including GPU passthrough, partitioning, and performance tuning across Nova, KVM/libvirt, and Kubernetes layers.
Assess customer and market requirements for hardware accelerators (GPUs, FPGAs) in AI/ML and HPC workloads, translating them into roadmap priorities for OpenShift and OpenStack virtualization platforms.
Develop and update project plans for OpenShift hardware enablement, defining technical objectives, system specifications (e.g., KMM, NFD), schedules, and cross‑functional staffing needs with RHEL, OpenStack, and hardware partners.
Prepare status reports on emerging hardware trends (GPU architectures, AI frameworks) and summarize progress on virtualization architecture requirements to inform platform strategy.
Establish and execute a communication plan to align cross‑departmental teams (RHEL, OpenShift, OpenStack) and external hardware vendors, ensuring transparency on accelerator roadmap execution and AI/ML workload support.
Submit production‑grade accelerator features (e.g., GPU support, resource scheduling) after validating scalability and security with engineering teams, ensuring compliance with enterprise infrastructure standards.
Direct the activities of engineering and quality personnel responsible for validating scalable, secure accelerator features, ensuring alignment with cloud‑native platform evolution.
Perform risk assessments on accelerator integration (e.g., driver compatibility, kernel‑level changes) and develop mitigation strategies for lifecycle management, upgrades, and secure boot compliance.
Develop a WBS for the delivery of Red Hat OpenStack Platform Compute and Cyborg components, breaking down tasks for GPU enablement, resource scheduling, and integration validation.
Negotiate with hardware partners (GPU vendors, FPGA suppliers) to obtain early access to accelerators and define joint roadmap commitments for AI/ML workload optimization.