About this opportunity
Engg lists this Senior HPC Cloud Engineer opportunity in hill air force base, Utah. Review the employer’s description below for duties, qualifications and application requirements.
Job description
At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands‑on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! Accenture Federal Services is seeking a Senior Cloud Engineer / HPC specialist to join our team and support our client at Hill AFB in Utah. This senior individual‑contributor role owns the design and operation of high‑performance compute infrastructure for mission workloads, from cluster architecture through GPU‑accelerated job scheduling. You will independently make cluster sizing and architecture decisions, mentor engineers, and partner with data platform and AI/ML teams to ensure infrastructure meets mission demand.
Success in This Role Means
HPC clusters are right‑sized and cost‑efficient, scaling compute and GPU resources to workload demand
Job scheduling (Slurm, PBS, AWS Batch/ParallelCluster) is reliable and self‑service, minimizing manual intervention
GPU‑accelerated workloads run efficiently, with proactive CUDA/cuDNN tuning and resource allocation
Data pipeline teams (Kafka, Airflow, Spark, EMR) have a stable, well‑documented compute foundation
Security and accreditation requirements for classified HPC workloads are met without impeding mission delivery
What you’ll do
Design, size, tune, and operate HPC clusters for compute‑intensive workloads
Own HPC job scheduling infrastructure (Slurm, PBS, or equivalent)
Architect/manage AWS ParallelCluster and/or AWS Batch for cloud‑based HPC provisioning
Design for parallel computing paradigms (MPI, shared‑memory, distributed task orchestration)
Configure industry GPU hardware/software for accelerated workloads
Tune CUDA, cuDNN, and GPU libraries for scientific computing/data processing
Optimize scheduling/resource allocation across CPU/GPU node pools
Integrate HPC compute with data pipelines (Kafka, Airflow, Spark) and AWS data services (EMR, Redshift, Glue)
Ensure HPC infrastructure meets security controls/accreditation for classified environments
Mentor engineers building HPC/GPU‑compute familiarity
Document cluster architecture decisions, runbooks, and operational procedures
What you’ll need
5 years’ cloud engineering/infrastructure experience, including 2 years focused on HPC cluster design/operations
Experience with HPC job scheduling systems (Slurm, PBS, or equivalent)
Proficiency with AWS ParallelCluster and/or AWS Batch for cloud‑based HPC provisioning
Understanding of parallel computing paradigms (e.g.: MPI, shared‑memory, distributed task orchestration)
Working knowledge of DevOps practices (e.g.: CI/CD, infrastructure‑as‑code, GitOps)
Scripting proficiency in Python, Bash, or PowerShell
Bonus Points if you have
Bachelor’s in Computer Science, Computational Science, Engineering, or related field (certifications considered in lieu)
Hands‑on experience with industry GPU hardware/software ecosystems
Familiarity with CUDA, cuDNN, and GPU‑accelerated libraries
Experience designing/operating data pipelines (Kafka, Airflow, Spark)
Familiarity with AWS data services (EMR, Redshift, Glue)
AWS certifications (Solutions Architect or Advanced Networking)
Work Environment & Culture Fit
Comfortable in fast‑paced, dynamic environments with evolving compute demands
Strong Agile framework familiarity (sprints, standups, retrospectives)
Solution ownership mindset—responsible for cluster efficiency/reliability
Fail‑fast, fail‑forward mentality—iterates on cluster tuning
Growth‑oriented—invested in mentoring engineers
Who Thrives in This Role
Extreme ownership mindset—accountable for cluster efficiency/workload reliability
Comfortable with ambiguity—translates vague mission needs into concrete architectures
Detail‑oriented on performance—tunes resource allocation to avoid over‑provisioning
Strong collaborator—partners with data engineering and AI/ML teams
Self‑directed—proactively identifies scaling/tuning opportunities
Why This Role Matters
Directly determines whether mission workloads—simulation, modeling, AI/ML pipelines—have the capacity and performance needed. Work is visible at every level, from data engineers and AI/ML teams to mission stakeholders relying on timely simulation and analysis results.
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia . The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience.
The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $109,500 - $224,200 USD
Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here.
Clearance: Must have an active Secret clearance; Top secret preferred
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Who can apply
Review the original listing for work authorization, qualifications and employer requirements.