Artificial Intelligence (AI) Engineer
Basic Qualifications Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience. Responsibilities for this Position What You'll Own Production AI services. Build and deploy agentic workflows, RAG pipelines, and LLM-integrated applications using Python, LangChain/LangGraph, and commercial foundation models (Claude, Codex, Gemini, open source). Data-to-insight pipelines. Implement document ingestion workflows that transform unstructured enterprise data into structured models for AI reasoning — embeddings, vectorization, knowledge graphs. API integration. Design and build secure API interfaces that connect AI services to internal tools, enterprise platforms (Oracle, IFS, Snowflake, PLM, MES, CRM), and data sources. Deployment and reliability. Containerize and deploy AI services using Docker and Kubernetes. Build monitoring and evaluation pipelines to track model reliability, latency, and operational performance. Prompt engineering at scale. Design, test, and optimize prompts and agent configurations for production use — not demos. What You Won't Own Platform architecture decisions — that's the Lead Architect's job Project coordination, scheduling, or status reporting Vendor evaluations or tool selection committees What Makes This Role Different You will build production AI systems for a 10,000-person enterprise — not prototypes, not demos, not proofs of concept You will work in a multi-model environment (Claude, Codex, Gemini, open source) on real enterprise problems — legacy modernization, ERP replacement, manufacturing intelligence AI-assisted development is the default workflow — Claude Code, Codex, agentic tooling. You will use AI to build AI. The team is small, the problems are hard, and your code ships to production. Your work will directly change how a major defense enterprise operates.
Required Qualifications
Bachelor’s degree in Computer Science, Software Engineering, or a related field, plus 5 years of experience; or Master’s degree plus 3 years of experience Production experience building applications with LLM APIs — you have deployed generative AI services that real users relied on, not just experimented with in notebooks Strong Python development skills — you write clean, testable, production-grade code, not scripts Experience with RAG pipelines, vector databases, and document ingestion workflows in production environments Experience building and consuming REST APIs — you have integrated AI services with enterprise systems and data platforms Containerized deployment experience — Docker, Kubernetes, CI/CD pipelines. You have shipped code through automated pipelines, not manual deployments. S. citizenship required. Department of Defense Secret security clearance is required at time of hire.
Preferred Qualifications
Experience with agent frameworks — LangChain, LangGraph, or similar tools for building multi-step, tool-using AI workflows Experience with multiple cloud platforms (AWS, Azure, GCP) including cloud-native AI services Hands-on use of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as part of your daily workflow Experience with streaming data pipelines (Kafka, Airflow) and production data infrastructure Model monitoring and evaluation — you have built systems to track AI service reliability, not just accuracy metrics in a notebook Commercial technology background — SaaS, healthcare, fintech, or platform engineering. Defense experience is not required. What Sets You Apart You build things that work. Your default response to a problem is code, not a document. You have shipped AI systems that real users depended on in production. You are comfortable working without detailed specs — you can take a problem statement and figure out the right approach. You care about reliability as much as capability — you monitor what you deploy. You move fast without being reckless. You know when to iterate and when to get it right the first time. Details Remote — 100% telework 9/80 schedule Defense industry experience is not required 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 $142,696.00 - USD $158,303.00 /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 Apply To This Job