AI ENGINEER

General Dynamics Information Technology; Maryland; Hybrid; USD 140,000 - 190,000; Full time

Job summary

General Dynamics Information Technology (GDIT) is seeking an AI Engineer to design, prototype, and integrate AI-enabled capabilities into mission-critical tools, with up to 3 days telework. The role emphasizes building agentic AI solutions, LLM integration, prompt engineering, and collaboration with system and software engineers to deliver robust AI-driven workflows for intelligence operations.

Applicants should have a Bachelor's degree, 8+ years of related experience, TS/SCI with Polygraph, and

Qualifications

• Bachelor's degree required.
• 8+ years of related experience.
• Security clearance level TS/ SCI W/ Polygraph.
• US citizenship required.

Responsibilities

• Lead design and development of AI-driven solutions from conception to deployment.
• Integrate existing foundation models into architecture via APIs and orchestration frameworks.
• Design prompts and workflows to automate tasks and decomposed steps for agents.
• Develop testing, evaluation, and validation strategies for AI outputs.
• Collaborate with system engineers, software developers, and domain experts.
• Stay current with evolving LLM and agentic AI landscape.

Skills

Python development

LLM integration

Multi-agent workflows

Prompt engineering

RESTful APIs

AWS

Education

Bachelor of Arts/Bachelor of Science

Tools

LangChain

LlamaIndex

Job description

AI ENGINEER

*** Up to 3 Days per week telework! ***

Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges as an AI Engineer.

MEANINGFUL WORK AND PERSONAL IMPACT

As an AI Engineer, the work you’ll do at GDIT will be impactful to the mission of a mission-critical customer. You will play a crucial role in designing, prototyping, and integrating AI-enabled capabilities into an existing mission - critical tool.

• Support the application of existing large language models (LLMs) to real mission workflows rather than training new models.
• Collaborate with system and software engineers
• Build agentic solutions, systems of coordinated AI agents and prompts that automate tasks currently performed manually, streamline authoring and reporting workflows, and enhance the overall effectiveness of intelligence operations.

WHAT YOU’LL NEED TO SUCCEED

Bring your expertise and drive for innovation to GDIT. The AI Engineer must have:

• Education: Bachelor of Arts/Bachelor of Science
• Experience: 8+ years of related experience
• Security clearance level: TS/ SCI W/ Polygraph
• US citizenship required

Responsibilities:

• Agentic Solution Design & Development: Lead the design and development of AI-driven solutions from conception to deployment, building multi-agent workflows in which coordinated agents and prompts work together to produce outputs supporting reporting and dissemination. This includes prototyping, writing production-quality code, and maintaining deployed AI capabilities.
• LLM Integration: Integrate existing foundation models into the RAD architecture via APIs and orchestration frameworks, selecting the right model and approach for each task rather than building models from scratch.
• Prompt Engineering & Workflow Automation: Design, test, and refine prompts and agent instructions to reliably automate manual tasks, and decompose complex mission workflows into discrete steps an agent pipeline can execute.
• Evaluation & Reliability: Develop robust testing, evaluation, and validation strategies for AI-generated outputs, ensuring accuracy, consistency, and appropriate handling of edge cases before outputs reach analysts and reports.
• Collaboration & Communication: Serve as a key technical liaison, collaborating with cross-functional teams including system engineers, software developers, and domain experts. Effectively present and articulate recommended AI approaches, discussing the tradeoffs and implications of different implementations with both technical and non-technical stakeholders.
• Continuous Improvement: Stay current with the rapidly evolving LLM and agentic AI landscape (new models, orchestration frameworks, and tooling), continuously identifying practical opportunities to apply emerging capabilities to the system.

Required Technical Skills:

• Strong Python development skills, with experience writing production-quality, maintainable code
• Hands-on experience building applications on top of existing LLMs (e.g., via APIs for commercial or self-hosted models)
• Experience designing multi-agent or multi-step AI workflows, including prompt chaining, tool use, and agent orchestration (e.g., LangChain, LlamaIndex, or custom frameworks)
• Strong prompt engineering skills and experience evaluating/validating LLM outputs
• Experience integrating AI capabilities into existing software architectures (RESTful APIs, microservices)
• Experience with the Amazon Web Services (AWS) cloud computing platform

Desired Technical Skills:

• Experience with retrieval-augmented generation (RAG) pipelines and vector databases
• Familiarity with LLM observability and evaluation tooling
• Experience conducting exploratory data analysis on structured and unstructured datasets to prepare inputs for AI workflows
• Familiarity with MLOps/LLMOps practices for deploying and monitoring AI capabilities at scale
• Familiarity with domain knowledge surrounding government agency reporting and dissemination policies

GDIT IS YOUR PLACE

At GDIT, the mission is our purpose, and our people are at the center of everything we do.

• Growth: AI-powered career tool that identifies career steps and learning opportunities
• Support: An internal mobility team focused on helping you achieve your career goals
• Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
• Community: Award-winning culture of innovation and a military-friendly workplace

OWN YOUR OPPORTUNITY

Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

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