AI Infrastructure Engineer

General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. They are seeking an AI Infrastructure Engineer to build the deployment backbone for a strategic initiative, focusing on automating data management and deploying applications using modern technologies like AI and Kubernetes.

Responsibilities:

• Use AI tools to analyze, map, and automate the data migration from the existing workflows and system
• Design modern, flexible data architectures, not locked to legacy patterns
• Leverage AI to detect data quality issues, validate migration results, and optimize database performance
• Partner with the development team to auto-tune queries and optimize storage architecture
• Build fully automated CI/CD pipelines with AI-powered testing, canary analysis, and automatic rollback
• Deploy and manage applications using Kubernetes and container orchestration with infrastructure-as-code
• Build self-healing systems that detect, diagnose, and resolve common issues automatically, only escalating truly novel problems to humans
• Automate environment provisioning, scaling, and configuration so nothing is done manually
• Use AI to automate operational tasks, eliminate manual, repetitive work that doesn't scale
• Build intelligent integration management between the new application and existing enterprise systems
• Leverage AI-assisted tools to generate, optimize, and maintain deployment tooling
• Auto-generate documentation from code, configurations, and system behavior
• Implement AI-powered observability that detects patterns, predicts failures, and suggests or executes fixes automatically
• Build systems where the lights rarely flicker, engineer reliability into the architecture, not bolt it on after
• Use AI to analyze incident patterns and build preventative measures that eliminate entire classes of failures
• Establish and track Service Level Objectives (SLOs) using automated data collection and reporting

Requirements:

• Requires a Bachelor's degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field
• Also requires 8+ years of job-related experience, or a Master's degree plus 6 years of job-related experience
• Department of Defense Secret security clearance is required at time of hire
• Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information
• Due to the nature of work performed within our facilities, U.S. citizenship is required
• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, plus a minimum of 5 years of relevant experience; or Master's degree plus a minimum of 3 years of relevant experience
• Demonstrated expertise with relational databases (Oracle, PostgreSQL, MySQL, or similar)
• Hands-on experience deploying and managing applications with Kubernetes
• Experience building and maintaining CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions, or similar)
• AWS RDS or other cloud-managed relational database services
• Cloud-managed Kubernetes (AWS EKS, Azure AKS, GCP EKS)
• Experience with data migration from legacy workflows and systems
• Proficiency with infrastructure-as-code tools (Terraform, Ansible, or similar)
• Experience with container technologies (Docker, Helm charts)
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack, or similar)
• Python scripting experience for automation and tooling
• Understanding of Site Reliability Engineering (SRE) principles
• Experience working in DoD or regulated environments