AI Infrastructure Engineer
About The Position
This is not a typical infrastructure job. You are building the deployment backbone for a strategic initiative that will define how GDMS builds and operates software going forward. The CI/CD pipelines, the data migration patterns, the production infrastructure you create here will become the blueprint for the future in-house development project. You'll build from scratch. No legacy infrastructure to inherit. You design it, you build it, you own it. You'll work with cutting-edge tools. AI-assisted development, modern deployment practices, Kubernetes orchestration this is a modern tech stack, not a legacy maintenance job. You'll have impact. Your work directly determines whether a mission-critical system succeeds in production. You'll have support. Leadership is fully committed to this initiative and will clear roadblocks so you can focus on engineering.
Requirements
- 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)
- 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.
- U.S. citizenship is required.
Nice To Haves
- Agile experience preferred.
- 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
- Identifies opportunities to apply AI for continuous improvement and innovation
Responsibilities
- Use AI tools to analyze, map, and automate the data migration from the existing workflows and systems
- 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
Benefits
- highly competitive benefits
- flexible work environment where contributions are recognized and rewarded
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
