Software Engineer Lead - GPU Platform Engineer

PNC•Strongsville, OH

1d•Onsite

About The Position

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Software Engineer Lead - GPU Platform Engineer within PNC's Data and Automation / Machine Learning Ops organization, you will be based in Pittsburgh, PA, Strongsville, OH, Dallas, TX, Birmingham, AL, Lakewood, CO or Phoenix, AZ. The Software Engineer Lead – GPU Platform Engineer is a senior, hands-on technical role responsible for designing, operating, and evolving large-scale GPU platform infrastructure. This role is intended for engineers with deep technical expertise who operate with a high degree of independence, take ownership of complex and ambiguous platform challenges, and provide technical leadership while remaining actively involved in implementation and operations.

Requirements

Advanced experience administering Linux systems in production environments
Strong hands-on experience with NVIDIA GPUs, drivers, and GPU compute technologies
Strong experience operating containerized platforms such as Docker and Kubernetes
Solid understanding of clustered, distributed, or HPC computing environments
Proficiency in Python for automation, tooling, and platform workflows
Experience with cluster schedulers such as Slurm and/or Kubernetes-based platforms (e.g., OpenShift)
Experience designing, deploying, or maintaining CI/CD pipelines for containerized platforms, including Helm
Experience deploying, scaling, or supporting multi-user platforms such as JupyterHub
Experience supporting GPU platforms in enterprise, highly available, or regulated environments
University / college degree, with 3+ years of relevant / direct industry experience. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Nice To Haves

Application Development
Business Management
Customer Solutions
Design
Docker Container
GPU Programming
Group Problem Solving
High-Performance Computing (HPC) Systems
Kubernetes
Process Improvements
Release Management
Software Solutions
User Experience (UX) Design

Responsibilities

Design, build, and operate large-scale, on‑premises GPU infrastructure
Lead advanced Linux system administration and platform initiatives
Architect, deploy, and operate containerized GPU workloads using Kubernetes and related tooling
Manage, optimize, and troubleshoot NVIDIA GPU environments at scale
Support and improve cluster scheduling, capacity planning, and resource management
Diagnose and resolve complex, cross-cutting, or poorly defined infrastructure issues
Collaborate closely with application, research, and infrastructure teams to enable GPU workloads and drive platform adoption
Take ownership of complex or ambiguous problems and drive them to resolution
Provide technical guidance, mentoring, and occasional leadership on platform design and operational decisions
Influence platform direction through hands-on expertise, architectural input, and operational insight
Drive continuous improvements in platform reliability, scalability, performance, and operational excellence

Benefits

medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service