Computing; HPC Engineer

Federal Reserve Bank of Kansas City

When you join the Federal Reserve—the nation's central bank—you’ll play a key role, collaborating with leading tech professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we’re building a dynamic and diverse team for our future.

• Open to US Citizens, Green Card holders or Permanent Residents with at least 3 years of residency, with the intent to become a US citizen.
• No sponsorship is available. Candidates must have valid work authorization, without an end date, to be considered.
• This position requires working on-site, in Kansas City, Denver, Oklahoma City or Omaha, with 5 days per month work from home flexibility. Relocation assistance is available.

The Center for the Advancement of Data and Research in Economics (CADRE) supports data and computationally intensive research and analytics for staff in the Economic Research division of the Federal Reserve Bank of Kansas City and across the Federal Reserve System. Our services include multiple high performance computing environments, research data warehousing, and advanced analytical tools. We are an embedded technology team within the division of Economic Research, Regional, and Community Affairs.

We are seeking an experienced High Performance Computing Engineer who can plan, implement, and maintain advanced cyberinfrastructure solutions. The ideal candidate will have deep expertise in HPC architectures, parallel computing frameworks, and scientific computing applications. You will work independently while collaborating with researchers to solve complex computational challenges that support critical economic research initiatives.

• Design, deploy, configure, and administer medium scale HPC clusters and associated storage systems.
• Monitor system health, performance metrics, and resource utilization to ensure optimal operation.
• Implement robust security protocols and perform regular maintenance including upgrades and patching.
• Troubleshoot complex hardware and software issues in a multi-user research environment.
• Manage job scheduling and workload optimization using tools like SLURM.
• Administer parallel file systems (such as Ceph and IBM Spectrum Scale/GPFS) and storage solutions.

• Design and implement innovative HPC solutions to address evolving research requirements.
• Create and maintain automation scripts and tools to streamline system administration.
• Optimize scientific applications and computational workflows for performance.
• Implement container technologies (Docker, Singularity) for reproducible research.
• Support GPU computing and accelerator technologies for specialized workloads.
• Define and track performance metrics to ensure efficient current and future use of resources.

• Partner closely with researchers to understand computational needs and translate them into technical solutions.
• Collaborate with network, security, and data center teams to ensure integrated operations.
• Build and maintain relationships with external vendors and technology partners.
• Participate in the HPC community to stay current with emerging technologies and best practices.
• Serve as a technical advisor on infrastructure planning and technology roadmaps.

• Develop comprehensive documentation for systems, policies, and procedures.
• Create user guides and training materials for researchers utilizing HPC resources.
• Provide mentorship to junior staff and knowledge sharing across teams.
• Conduct workshops and training sessions on effective use of HPC resources.

• Bachelor’s degree in computer science, engineering, mathematics, or related field, or equivalent combination of education and experience.
• Minimum of 6 years of relevant experience in HPC administration and systems engineering.
• Extensive experience with Linux operating systems (Red Hat/CentOS) in an HPC environment.
• Strong command line skills and proficiency in scripting languages (Python, Bash).
• Experience with job scheduling systems (SLURM,…