AI Engineer with TS/SCI Clearance & Full Scope Polygraph - Hybrid role in Annapolis Junction

bookerdimaio; Maryland; Hybrid; USD 120,000 - 190,000; Full time

Job summary

bookerdimaio is seeking an AI Engineer with an active TS/SCI Full Scope Polygraph for a hybrid role in Maryland. You will design agentic AI solutions, integrate LLMs, and automate mission workflows to support intelligence reporting.

Work with system and software engineers to prototype and deploy AI capabilities, focusing on prompt engineering, multi-agent orchestration, and reliable outputs. Remote up to 3 days/week, onsite 2 days/week in Annapolis Junction, MD.

Qualifications

• Strong Python development with production-quality code.
• Hands-on experience building apps on top of existing LLMs via APIs.
• Experience designing multi-agent or multi-step AI workflows and orchestration.
• Strong prompt engineering and evaluation of LLM outputs.
• Experience integrating AI capabilities into software architectures (RESTful APIs).
• Experience with AWS cloud platform.

Responsibilities

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

Skills

Python

Production-quality code

LLM applications

Multi-agent workflows

Prompt engineering

RESTful APIs

AWS

Tools

LangChain

LlamaIndex

API orchestration

AWS

Job description

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