AI Integration Engineer with Security Clearance

160-230k Must Haves:
• Active Top-Secret Clearance with ability to obtain/maintain TS/SCI
• 5+ years of experience in Systems Engineering, Platform Engineering, Infrastructure Engineering, DevSecOps, Cloud Engineering, or related technical environments • Experience deploying, integrating, or supporting software applications within production environments • Experience supporting cloud-based platforms in AWS, Azure, or similar environments • Experience with Docker and Kubernetes • Experience integrating applications, APIs, or distributed services • Linux administration and troubleshooting experience • Strong understanding of networking fundamentals (TCP/IP, DNS, routing, load balancing, firewalls) • Strong troubleshooting and problem-solving skills
Preferred Qualifications: • Active TS/SCI or Polygraph • Experience supporting Large Language Models (LLMs), Generative AI, Machine Learning, or AI-enabled applications
• Experience supporting MLOps pipelines and deployment frameworks
• Experience with MLflow, Kubeflow, TensorFlow Serving, LangSmith, Arize Phoenix, or similar technologies
• Experience with GPU-enabled environments, high-performance computing, or AI infrastructure platforms
• Experience with Infrastructure as Code tools such as Terraform or Pulumi
• Experience supporting PostgreSQL, Redis, vector databases, or other modern data platforms
• Experience working within cyber, intelligence, defense, or national security organizations
• Previous military experience within cyber, intelligence, communications, networking, or technical operations communities
• Experience supporting customer-facing implementation, integration, or deployment efforts
Job Description:
Insight Global is seeking an AI Systems Engineer to support the deployment, integration, and sustainment of AI-enabled applications within customer and mission-focused environments. This individual will serve as a key technical contributor responsible for helping transition emerging AI technologies from development and prototype environments into operational use. The ideal candidate possesses a strong background in systems engineering, cloud technologies, application integration, infrastructure management, and platform operations, with the ability to work across multiple technologies and evolving mission requirements.
The selected candidate will work closely with software engineers, AI/ML engineers, architects, and technical leadership to deploy scalable environments, integrate applications into customer ecosystems, and maintain the infrastructure necessary to support reliable operations. Successful candidates will be comfortable troubleshooting complex issues, supporting distributed systems, and enabling the successful deployment of AI-driven capabilities into production environments. This role is ideal for someone who enjoys solving challenging technical problems, working directly with stakeholders, and helping bridge the gap between innovative technology development and real-world implementation. Additional Responsibilities:
• Deploy and integrate AI-enabled applications within cloud, hybrid, and customer-operated environments
• Support platform architecture, infrastructure components, and application connectivity across multiple systems
• Manage and maintain containerized environments using Docker and Kubernetes
• Implement and support CI/CD pipelines to streamline software deployment and operational efficiency
• Monitor, troubleshoot, and optimize system performance, reliability, and availability
• Support infrastructure automation, configuration management, and scalability initiatives
• Collaborate with software engineering, AI/ML, and systems engineering teams throughout the deployment lifecycle
• Evaluate and integrate emerging technologies into existing operational environments
• Assist with customer-facing deployment, integration, testing, and troubleshooting efforts
• Support secure, mission-critical environments requiring high levels of reliability and operational excellence