{"schemaVersion":"jobsearcher.job.v1","id":"d9c02b001ebbcfc05dcb9fdd","url":"https://jobsearcher.com/jobs/d9c02b001ebbcfc05dcb9fdd","canonicalUrl":"https://jobsearcher.com/jobs/d9c02b001ebbcfc05dcb9fdd","title":"Artificial Intelligence (AI) Engineer","description":"Basic Qualifications :\nBachelor'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.\n\nCLEARANCE REQUIREMENTS:: 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.\nResponsibilities for this Position:\nWhat You'll Own\nProduction 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).\nData-to-insight pipelines. Implement document ingestion workflows that transform unstructured enterprise data into structured models for AI reasoning — embeddings, vectorization, knowledge graphs.\nAPI 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.\nDeployment and reliability. Containerize and deploy AI services using Docker and Kubernetes. Build monitoring and evaluation pipelines to track model reliability, latency, and operational performance.\nPrompt engineering at scale. Design, test, and optimize prompts and agent configurations for production use — not demos.\nWhat You Won't Own\nPlatform architecture decisions — that's the Lead Architect's job\nProject coordination, scheduling, or status reporting\nVendor evaluations or tool selection committees\nWhat Makes This Role Different\nYou will build production AI systems for a 10,000-person enterprise — not prototypes, not demos, not proofs of concept\nYou will work in a multi-model environment (Claude, Codex, Gemini, open source) on real enterprise problems — legacy modernization, ERP replacement, manufacturing intelligence\nAI-assisted development is the default workflow — Claude Code, Codex, agentic tooling. You will use AI to build AI.\nThe team is small, the problems are hard, and your code ships to production. Your work will directly change how a major defense enterprise operates.\nRequired Qualifications\nBachelor’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\nProduction experience building applications with LLM APIs — you have deployed generative AI services that real users relied on, not just experimented with in notebooks\nStrong Python development skills — you write clean, testable, production-grade code, not scripts\nExperience with RAG pipelines, vector databases, and document ingestion workflows in production environments\nExperience building and consuming REST APIs — you have integrated AI services with enterprise systems and data platforms\nContainerized deployment experience — Docker, Kubernetes, CI/CD pipelines. You have shipped code through automated pipelines, not manual deployments.\nU.S. citizenship required. Department of Defense Secret security clearance is required at time of hire.\nPreferred Qualifications\nExperience with agent frameworks — LangChain, LangGraph, or similar tools for building multi-step, tool-using AI workflows\nExperience with multiple cloud platforms (AWS, Azure, GCP) including cloud-native AI services\nHands-on use of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as part of your daily workflow\nExperience with streaming data pipelines (Kafka, Airflow) and production data infrastructure\nModel monitoring and evaluation — you have built systems to track AI service reliability, not just accuracy metrics in a notebook\nCommercial technology background — SaaS, healthcare, fintech, or platform engineering. Defense experience is not required.\nWhat Sets You Apart\nYou build things that work. Your default response to a problem is code, not a document.\nYou have shipped AI systems that real users depended on in production.\nYou are comfortable working without detailed specs — you can take a problem statement and figure out the right approach.\nYou care about reliability as much as capability — you monitor what you deploy.\nYou move fast without being reckless. You know when to iterate and when to get it right the first time.\nDetails\nRemote — 100% telework\n9/80 schedule\nDefense industry experience is not required\nSalary 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:\nGeneral 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!\n\nEqual Opportunity Employer / Individuals with Disabilities / Protected Veterans","company":"General Dynamics Mission Systems","rawCompany":"general dynamics mission systems","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-06T15:07:41.497Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Artificial Intelligence (AI) Engineer","description":"Basic Qualifications :\nBachelor'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.\n\nCLEARANCE REQUIREMENTS:: 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.\nResponsibilities for this Position:\nWhat You'll Own\nProduction 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).\nData-to-insight pipelines. Implement document ingestion workflows that transform unstructured enterprise data into structured models for AI reasoning — embeddings, vectorization, knowledge graphs.\nAPI 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.\nDeployment and reliability. Containerize and deploy AI services using Docker and Kubernetes. Build monitoring and evaluation pipelines to track model reliability, latency, and operational performance.\nPrompt engineering at scale. Design, test, and optimize prompts and agent configurations for production use — not demos.\nWhat You Won't Own\nPlatform architecture decisions — that's the Lead Architect's job\nProject coordination, scheduling, or status reporting\nVendor evaluations or tool selection committees\nWhat Makes This Role Different\nYou will build production AI systems for a 10,000-person enterprise — not prototypes, not demos, not proofs of concept\nYou will work in a multi-model environment (Claude, Codex, Gemini, open source) on real enterprise problems — legacy modernization, ERP replacement, manufacturing intelligence\nAI-assisted development is the default workflow — Claude Code, Codex, agentic tooling. You will use AI to build AI.\nThe team is small, the problems are hard, and your code ships to production. Your work will directly change how a major defense enterprise operates.\nRequired Qualifications\nBachelor’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\nProduction experience building applications with LLM APIs — you have deployed generative AI services that real users relied on, not just experimented with in notebooks\nStrong Python development skills — you write clean, testable, production-grade code, not scripts\nExperience with RAG pipelines, vector databases, and document ingestion workflows in production environments\nExperience building and consuming REST APIs — you have integrated AI services with enterprise systems and data platforms\nContainerized deployment experience — Docker, Kubernetes, CI/CD pipelines. You have shipped code through automated pipelines, not manual deployments.\nU.S. citizenship required. Department of Defense Secret security clearance is required at time of hire.\nPreferred Qualifications\nExperience with agent frameworks — LangChain, LangGraph, or similar tools for building multi-step, tool-using AI workflows\nExperience with multiple cloud platforms (AWS, Azure, GCP) including cloud-native AI services\nHands-on use of AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as part of your daily workflow\nExperience with streaming data pipelines (Kafka, Airflow) and production data infrastructure\nModel monitoring and evaluation — you have built systems to track AI service reliability, not just accuracy metrics in a notebook\nCommercial technology background — SaaS, healthcare, fintech, or platform engineering. Defense experience is not required.\nWhat Sets You Apart\nYou build things that work. Your default response to a problem is code, not a document.\nYou have shipped AI systems that real users depended on in production.\nYou are comfortable working without detailed specs — you can take a problem statement and figure out the right approach.\nYou care about reliability as much as capability — you monitor what you deploy.\nYou move fast without being reckless. You know when to iterate and when to get it right the first time.\nDetails\nRemote — 100% telework\n9/80 schedule\nDefense industry experience is not required\nSalary 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:\nGeneral 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!\n\nEqual Opportunity Employer / Individuals with Disabilities / Protected Veterans","datePosted":"2026-08-06T15:07:41.497Z","dateModified":"2026-08-06T15:07:41.497Z","hiringOrganization":{"@type":"Organization","name":"General Dynamics Mission Systems","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d9c02b001ebbcfc05dcb9fdd"},"url":"https://jobsearcher.com/jobs/d9c02b001ebbcfc05dcb9fdd"}}