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Lead Software & AI Engineer Position Overview G2IT is seeking a highly skilled Lead Software & AI Engineer to support mission-critical Department of Defense initiatives. The ideal candidate will possess extensive experience in software engineering, cloud-native application development, DevSecOps, and Artificial Intelligence/Machine Learning (AI/ML) integration within operational environments. This position requires a technical leader capable of designing, developing, and deploying advanced software solutions while integrating Machine Learning, Artificial Intelligence, and Large Language Models (LLMs) into secure enterprise and mission systems. Security Clearance Requirements Active Top Secret/SCI clearance or TS/SCI eligibility with a completed Tier 5 investigation at the time of submission. Required Qualifications Minimum five (5) years of hands-on experience developing and supporting microservices-based architectures. Minimum five (5) years of experience with containerized applications and Kubernetes-based environments. Demonstrated experience developing, integrating, or deploying Machine Learning (ML), Artificial Intelligence (AI), and/or Large Language Models (LLMs) within operational systems. DoD 8140/8570 IAT Level II certification and/or intermediate proficiency baseline certification for Cyber Workforce Framework (CSWF) approval, such as: Security+ CE CySA+ Equivalent approved certification Strong understanding of secure software development practices and DevSecOps methodologies. Excellent analytical, problem-solving, communication, and leadership skills. Key Responsibilities Lead the design, development, integration, and deployment of cloud-native software solutions supporting mission-critical operations. Architect and implement AI/ML and LLM-enabled capabilities within enterprise and operational systems. Design and develop scalable microservices and APIs using modern software engineering practices. Collaborate with government and contractor stakeholders to define technical requirements and deliver innovative solutions. Provide technical leadership, mentorship, and guidance to development and engineering teams. Support system modernization efforts through automation, cloud adoption, and DevSecOps best practices. Ensure security, scalability, reliability, and maintainability across all software solutions. Technical Requirements Artificial Intelligence & Machine Learning Experience developing, integrating, and operationalizing: Machine Learning models Artificial Intelligence solutions Large Language Models (LLMs) AI-enabled workflows and applications Familiarity with modern AI frameworks, model deployment, inference pipelines, and retrieval-augmented generation (RAG) architectures is highly desirable. Containerization & Orchestration Experience implementing and managing containerized applications using: Docker Podman Buildah Experience designing and maintaining orchestration platforms utilizing: Kubernetes OpenShift Helm DevSecOps & CI/CD Experience developing and optimizing CI/CD pipelines using: GitLab Jenkins AWS CodeBuild Strong understanding of automated testing, deployment, and release management processes. Infrastructure as Code & Automation Experience automating infrastructure provisioning and configuration management using: Terraform Ansible AWS CloudFormation Experience implementing repeatable and scalable infrastructure solutions. Linux Systems Administration Experience administering and supporting Linux-based environments including: Red Hat Enterprise Linux (RHEL) CentOS Ubuntu Scripting & Automation Experience creating automation tools and operational scripts using: Bash Python PowerShell Cloud Platforms Experience designing, deploying, and maintaining applicat