Basic Qualifications
Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience. Agile experience preferred.
Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
ROLE AND POSITION OBJECTIVES:
As an AI Automation Engineer for our AIOps team, you'll be a core member of a high-performing, cross-functional team responsible for modernizing critical enterprise systems through intelligent automation, AI-powered infrastructure, agentic AI workflows, and secure, scalable deployment pipelines. You won't just write scripts — you'll engineer complete automation solutions from the ground up, integrating AI agents, Model Context Protocol (MCP) servers, and intelligent tooling into every layer of the stack.
We encourage you to apply if you have any of these preferred skills or experiences:
- Proven experience building end-to-end automation solutions using tools like GitLab CI, Kubernetes, Terraform, and Ansible — not just scripting, but full lifecycle design and implementation.
- Hands-on expertise deploying and managing containerized applications with Kubernetes and automating infrastructure provisioning with Terraform and Ansible in an AIOps environment.
- Experience building and owning CI/CD pipelines end-to-end, leveraging GitLab CI and AI-powered tools to automate testing, deployment, and operational workflows
- Experience designing, deploying, and managing MCP (Model Context Protocol) servers to expose tools, data sources, and APIs as context for AI agents and LLM-powered workflows
- Familiarity with OAuth 2.0 / OpenID Connect authentication flows within MCP servers, including token management, scoped permissions, and secure delegation of access to downstream services
- Hands-on experience building or integrating AI agent skills — defining tool-use capabilities, orchestrating multi-step agentic workflows, and enabling agents to autonomously interact with infrastructure, CI/CD pipelines, and operational systems
- Experience working with or deploying AI/ML models, LLM-based assistants, and agentic frameworks (e.g., Claude Agent SDK, A2A, ACP, or similar) in production or operational environments
- Understanding of prompt engineering, retrieval-augmented generation (RAG), and how to ground AI agents with real-time enterprise context via MCP or similar protocols
What Sets You Apart:
- You write code to solve problems — if you're doing something manually more than twice, you're already automating it with GitLab CI, Terraform, Ansible, Kubernetes, or an AI agent
- Deep expertise in end-to-end automation, from CI/CD pipeline design to self-healing infrastructure, container orchestration, and proactive reliability engineering — increasingly augmented by AI-driven decision-making and agentic automation
- Strong understanding of AIOps principles with operational intelligence embedded at every layer — infrastructure-as-code, automated compliance checks, secure pipeline design, and secure AI integration including OAuth-secured MCP servers and least-privilege agent access patterns
- Experience architecting MCP server ecosystems that allow AI agents to securely query databases, trigger deployments, inspect infrastructure state, and interact with third-party APIs — all governed by robust authentication and authorization
- Experience building custom agent skills and tool definitions that enable AI agents to perform complex, multi-step operations across your AIOps toolchain autonomously and reliably
- Experience working in complex, regulated, or mission-critical environments where Kubernetes, Terraform, automated deployments, and AI-augmented operations are the standard, not the exception
- A builder's mindset — you don't maintain the status quo, you transform it with the right tools, the right code, and the right AI agents working alongside your team
- Identifies opportunities to apply AI for continuous improvement and innovation
Our Commitment to You:
- An exciting career path with opportunities for continuous learning and development.
- Research oriented work, alongside award winning teams developing practical solutions for our nation’s security
- Flexible schedules with every other Friday off work, if desired (9/80 schedule)
- Competitive benefits, including 401k matching, flex time off, paid parental leave, healthcare benefits, health & wellness programs, employee resource and social groups, and more
- See more at gdmissionsystems.com/careers/why-work-for-us/benefits
Workplace Options:This position is fully remote/telework OR Hybrid/Flex as desired.
#AI
Salary Note
This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.Combined Salary Range
USD $124,397.00 - USD $138,003.00 /Yr.Company Overview
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. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans
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