Location: Annapolis Junction, MD (100% on-site)

Clearance: Active TS/SCI with Full Scope Polygraph (within the last 7 years)

About EITR Technologies

EITR Technologies was built by technologists who are still billable today. We know what it means to be on-site and on-contract in the government space, and we built the company we always wished we worked for.

We're small on purpose. You won't be five layers deep in an org chart; you'll work directly with company leadership and senior government stakeholders, and you'll have a real say in our technical direction, tooling, and culture. Good ideas here turn into actual company offerings. We offer strong pay, industry-leading benefits, and a culture with no strings attached: come to our happy hours and game nights if you want, skip them if you don't. We hire adults and treat them like it.

About the Role

We're hiring a Software Integration Engineer to bring analytic software and mission workloads onto large high performance computing (HPC) and high performance data analytics (HPDA) environments supporting national security missions. The scale of compute, storage, and interconnect in these environments is unusual even by HPC standards, and getting software to run well at that scale is a genuine engineering problem, not a deployment checklist.

You'll sit at the intersection of software, platform, and mission: taking code from development teams and making it perform on production clusters, GPU resources, and hybrid cloud platforms; building the automation and pipelines that keep those workloads flowing; and helping evaluate emerging technologies in a lab environment before they reach mission networks. The work involves close collaboration with government stakeholders, developers, system administrators, engineers across multiple disciplines, and the OEMs whose gear the program runs.

What You'll Do

• Integrate, deploy, and troubleshoot analytic software across HPC and HPDA environments, working in Python, C/C++, and Java as the codebase demands

• Build and maintain data engineering pipelines that move and prepare data at scale across high-performance storage and distributed computing platforms

• Containerize and orchestrate workloads with Kubernetes, and support their deployment across on-prem clusters and cloud/hybrid cloud platforms

• Optimize workloads for distributed and GPU-accelerated execution, profiling performance and working bottlenecks in code, storage, and network paths

• Develop and maintain automation frameworks for building, testing, and deploying software, reducing manual integration work across environments

• Troubleshoot integration issues that cross software, platform, and infrastructure boundaries, working alongside system administrators and developers to isolate root causes

• Support migration and modernization efforts as workloads move between on-prem HPC and cloud platforms

• Help evaluate emerging compute, storage, and data analytics technologies in a lab environment, assessing how mission software performs on new platforms before they're fielded

Required Qualifications

• 5–10+ years of experience supporting High Performance Data Analytics (HPDA) and/or High Performance Computing (HPC) environments

• Strong Linux skills and hands-on programming experience in Python and at least one of C, C++, or Java

• Experience with distributed computing and integrating or deploying software at scale

• Experience with one or more of the following: Kubernetes, cloud/hybrid cloud platforms, GPU acceleration, automation frameworks, high-performance storage, or data engineering pipelines

• DoD 8570 IAT Level I certification (e.g., A+ CE, Network+ CE, SSCP) — current, or ability to obtain prior to start

• Active TS/SCI clearance with Full Scope Polygraph completed within the last 7 years

Nice to Have

• Experience with parallel file systems (Lustre, GPFS) or other HPC-specific storage and interconnect infrastructure

• Familiarity with HPC workload managers/schedulers (e.g., Slurm, PBS) and how software behaves under them

• Experience with GPU programming or acceleration frameworks (e.g., CUDA) and performance profiling tools

• CI/CD pipeline experience (e.g., GitLab CI, Jenkins) in accredited or air-gapped environments

• Experience with infrastructure-as-code and configuration management (e.g., Ansible, Terraform)

• Experience evaluating pre-production or emerging technologies in lab environments

Growth

This role is a strong fit for a software engineer who wants their code running on systems most engineers never see. At a company our size, the path from integration engineer to lead, architect, or customer-facing roles is short and based entirely on performance.