<div class="content-intro"><div> <div> </div> <div>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. </div> <div> </div> <div>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. </div> <div> </div> <div>Join us to drive positive, lasting change that moves missions and the government forward!</div> <div> </div> </div></div><p>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.</p> <p><strong>Success in This Role Means: </strong></p> <ul> <li>HPC clusters are right-sized and cost-efficient, scaling compute and GPU resources to workload demand</li> <li>Job scheduling (Slurm, PBS, AWS Batch/ParallelCluster) is reliable and self-service, minimizing manual intervention</li> <li>GPU-accelerated workloads run efficiently, with proactive CUDA/cuDNN tuning and resource allocation</li> <li>Data pipeline teams (Kafka, Airflow, Spark, EMR) have a stable, well-documented compute foundation</li> <li>Security and accreditation requirements for classified HPC workloads are met without impeding mission delivery</li> </ul> <p><strong>What you’ll do: </strong></p> <ul> <li>Design, size, tune, and operate HPC clusters for compute-intensive workloads</li> <li>Own HPC job scheduling infrastructure (Slurm, PBS, or equivalent)</li> <li>Architect/manage AWS ParallelCluster and/or AWS Batch for cloud-based HPC provisioning</li> <li>Design for parallel computing paradigms (MPI, shared-memory, distributed task orchestration)</li> <li>Configure industry GPU hardware/software for accelerated workloads</li> <li>Tune CUDA, cuDNN, and GPU libraries for scientific computing/data processing</li> <li>Optimize scheduling/resource allocation across CPU/GPU node pools</li> <li>Integrate HPC compute with data pipelines (Kafka, Airflow, Spark) and AWS data services (EMR, Redshift, Glue)</li> <li>Ensure HPC infrastructure meets security controls/accreditation for classified environments</li> <li>Mentor engineers building HPC/GPU-compute familiarity</li> <li>Document cluster architecture decisions, runbooks, and operational procedures</li> </ul> <p><strong>What you’ll need: </strong></p> <ul> <li>5 years’ cloud engineering/infrastructure experience, including 2 years focused on HPC cluster design/operations</li> <li>Experience with HPC job scheduling systems (Slurm, PBS, or equivalent)</li> <li>Proficiency with AWS ParallelCluster and/or AWS Batch for cloud-based HPC provisioning</li> <li>Understanding of parallel computing paradigms (e.g.: MPI, shared-memory, distributed task orchestration)</li> <li>Working knowledge of DevOps practices (e.g.: CI/CD, infrastructure-as-code, GitOps)</li> <li>Scripting proficiency in Python, Bash, or PowerShell</li> </ul> <p><strong>Bonus Points if you have: </strong></p> <ul> <li>Bachelor’s in Computer Science, Computational Science, Engineering, or related field (certifications considered in lieu)</li> <li>Hands-on experience with industry GPU hardware/software ecosystems</li> <li>Familiarity with CUDA, cuDNN, and GPU-accelerated libraries</li> <li>Experience designing/operating data pipelines (Kafka, Airflow, Spark)</li> <li>Familiarity with AWS data services (EMR, Redshift, Glue)</li> <li>AWS certifications (Solutions Architect or Advanced Networking)</li> </ul> <p><strong>Clearance: </strong></p> <ul> <li>Must have an active Secret clearance; Top secret preferred</li> </ul> <p><em>Work Environment & Culture Fit </em></p> <ul> <li>Comfortable in fast-paced, dynamic environments with evolving compute demands</li> <li>Strong Agile framework familiarity (sprints, standups, retrospectives)</li> <li>Solution ownership mindset—responsible for cluster efficiency/reliability</li> <li>Fail-fast, fail-forward mentality—iterates on cluster tuning</li> <li>Growth-oriented—invested in mentoring engineers</li> </ul> <p><em>Who Thrives in This Role </em></p> <ul> <li>Extreme ownership mindset—accountable for cluster efficiency/workload reliability</li> <li>Comfortable with ambiguity—translates vague mission needs into concrete architectures</li> <li>Detail-oriented on performance—tunes resource allocation to avoid over-provisioning&