AI Engineer with TS/SCI Clearance & Full Scope Polygraph - Hybrid role in Annapolis Junction
Annapolis Junction Full-time Mid-level AI Engineering
At a glance
Mid-level AI Engineering role at Booker DiMaio. Annapolis Junction · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Estimated pay
Booker DiMaio has not published a salary for this role. The figure below is our estimate, not theirs.
$132,450 – $205,151
What the middle half of mid-level AI engineering roles in the United States paid, among postings that did state a salary.
Worked out from 376 postings that stated pay, median $165,000. Last updated Oct 22, 2026.
RoleAI Engineering
SeniorityMid-level
LocationAnnapolis Junction
EmploymentFull-time
PostedSep 4, 2026 · 6w ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Develop agent systems that combine prompts and coordinated steps to support intelligence reporting and dissemination
- Connect existing language models to software through APIs and orchestration tools, matching the approach to each task
- Break manual mission work into agent-executable steps, then refine prompts to automate those workflows
- Check generated results for accuracy, consistency and edge cases before analysts rely on them
- Build, deploy and maintain production code with system engineers, software developers and domain experts
What you bring
- You hold a current Top Secret/SCI clearance and Full Scope Polygraph
- You bring strong Python skills and a record of writing maintainable, production-ready code
- You have built applications with existing LLMs and designed coordinated agent workflows, including prompt chaining or tool use
- You have integrated AI into software using REST APIs or microservices, and have experience with AWS
Who this fits
This role suits an AI engineer focused on applying existing language models to mission workflows rather than training models. You’ll collaborate with technical teams and domain experts, and explain implementation choices to both technical and non-technical audiences. The hybrid schedule includes up to three remote days and two onsite days each week in Annapolis Junction, Maryland.
From the employer
An active Top Secret/SCI Clearance with a Full Scope Polygraph is required.
This is a hybrid schedule with up to 3 days/week remote and 2 days/week onsite in Annapolis Junction, MD.
We have an immediate need for an Artificial Intelligence (AI) Engineer to support the development and sustainment of mission-focused AI capabilities. The AI Engineer will work closely with system and software engineers to design, prototype, and integrate AI-enabled capabilities into existing software architectures. This role centers on applying existing large language models (LLMs) to real mission workflows rather than training new models. The AI Engineer will 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.
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 existing software architectures 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
This is a hybrid schedule with up to 3 days/week remote and 2 days/week onsite in Annapolis Junction, MD.
We have an immediate need for an Artificial Intelligence (AI) Engineer to support the development and sustainment of mission-focused AI capabilities. The AI Engineer will work closely with system and software engineers to design, prototype, and integrate AI-enabled capabilities into existing software architectures. This role centers on applying existing large language models (LLMs) to real mission workflows rather than training new models. The AI Engineer will 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.
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 existing software architectures 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