Expert Systems Engineer

CACI•Fayetteville, NC
•$108,900 - $239,500

About The Position

CACI is seeking an Expert Systems Engineer to apply creative, nontraditional approaches to large-scale enterprise systems engineering in support of artificial intelligence, machine learning, and high-performance computing technologies. The role develops cross-cutting solutions that integrate and optimize disparate data sources, methods, and technologies; translates academic research and commercial best practices into sustainable analytic workflows; incorporates emerging capabilities; and designs solutions accessible to nontechnical users. The work supports teams in interpreting complex data, identifying relationships, anticipating outcomes, and producing actionable intelligence for mission support. The position is full-time and requires an active Top Secret clearance with eligibility for Sensitive Compartmented Information access. It requires a bachelor’s degree in a related field and at least 10 years of professional experience, or at least 15 years of progressive systems engineering experience supporting DoW or IC IT infrastructure and architecture. The proposed salary range is $108,900–$239,500. Travel is up to 10%, local. CACI describes a culture of integrity and trust, flexible time off, learning resources, and comprehensive benefits and development opportunities.

Requirements

  • Active Top Secret security clearance with eligibility for access to Sensitive Compartmented Information (SCI).
  • Bachelor’s degree in computer science, electrical engineering, or a related field and at least 10 years of professional experience; or at least 15 years of progressive systems engineering experience managing IT infrastructure and architecture in support of the Department of War (DoW) or Intelligence Community (IC).
  • Demonstrated systems engineering experience emphasizing AI and machine learning optimization.
  • Strong knowledge of server, storage, and supercomputing architectures.
  • Expertise in networking protocols and high-performance computing environments.
  • Experience with GPU optimization and parallel processing.
  • Proficiency in storage configuration and management.
  • Familiarity with AI and machine learning frameworks and libraries such as TensorFlow and PyTorch.
  • Excellent problem-solving skills and attention to detail.
  • Strong written and verbal communication and collaboration skills.
  • Ability to obtain and maintain the applicable certification required under DoD 8140.

Nice To Haves

  • Master’s degree in computer science, electrical engineering, or a related field.
  • Experience with cloud computing platforms such as AWS, Microsoft Azure, or Google Cloud.
  • Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
  • Experience with version control systems such as Git.
  • Strong knowledge of geographic information system (GIS) software and tools such as ArcGIS, QGIS, and GeoServer.
  • Experience with geospatial data formats including Shapefile, GeoJSON, and KML.
  • Familiarity with web mapping technologies such as Leaflet and OpenLayers.

Responsibilities

  • Work with a multidisciplinary team to solve operational challenges involving data analytics and mission support.
  • Design, implement, and maintain high-performance computing environments for AI and machine learning applications.
  • Optimize server, GPU, and supercomputing configurations for efficiency, scalability, reliability, and performance.
  • Develop networking solutions for high-throughput data processing and distributed workloads.
  • Configure and manage storage systems for reliable, efficient data access and retrieval.
  • Collaborate with data scientists and engineers to integrate AI and machine learning models into production environments.
  • Monitor system performance, troubleshoot bottlenecks, and identify opportunities for continuous improvement.
  • Evaluate advances in AI, machine learning, and high-performance computing and incorporate relevant capabilities into enterprise systems.

Benefits

  • Flexible time off benefit.
  • Learning resources and learning and development opportunities.
  • Comprehensive benefits, including healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
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