Artificial Intelligence Engineer
About The Position
DAn Solutions is seeking an experienced Artificial Intelligence Engineer to design, develop, and deploy secure AI systems that integrate foundation models with enterprise tools, data sources, and mission services. The role focuses on production-grade agentic AI architectures, advanced retrieval systems, and stateful orchestration workflows in secure enterprise environments. It requires knowledge of AI engineering, distributed systems, identity-based access controls, and operational reliability. The position is full-time and on-site at a government facility in Charleston, SC, or the National Capital Region. An active TS/SCI clearance is required, with the ability to obtain a CI Polygraph. Compensation depends on the applicable Labor Category and factors including education, relevant experience, certifications, and other required qualifications; no salary figures are provided.
Requirements
- Active TS/SCI clearance and ability to obtain a CI Polygraph.
- Bachelor's degree in Cybersecurity, Computer Engineering, Electrical Engineering, Mathematics, or a related technical discipline, or equivalent qualifications.
- At least 5 years of relevant professional experience.
- Hands-on production experience with MCP server/client implementations and agent orchestration frameworks.
- Experience with LangGraph, CrewAI, and Claude Agent SDK.
- Demonstrated experience developing GraphRAG, dynamic query routing, and advanced retrieval pipelines.
- Strong understanding of context compression, state management, and session persistence.
- Experience using JSON Schema and Protocol Buffers.
- Experience integrating IAM tokens, claims, and access controls into AI systems.
- Experience designing reliable distributed systems with retry controls, execution limits, and recovery mechanisms.
- Experience implementing Human-in-the-Loop approval and execution workflows.
- Ability to work full-time on-site at a government facility.
Nice To Haves
- Master's degree in a related technical discipline.
- Experience evaluating agent behavior and implementing observability tools such as OpenTelemetry, LangSmith, or Arize Phoenix.
- Experience with automated red-teaming and security testing for AI systems.
- Background deploying AI systems in highly regulated or mission-critical environments.
- Strong Python, TypeScript, or Go programming skills.
- Experience developing high-performance MCP servers and custom orchestration runtimes.
Responsibilities
- Design and implement secure, modular agentic AI architectures.
- Integrate foundation models with enterprise tools and services using the Model Context Protocol (MCP).
- Develop stateful agent workflows using LangGraph, CrewAI, Claude Agent SDK, or comparable frameworks.
- Build advanced retrieval systems using GraphRAG, agentic routing, and Corrective RAG.
- Develop context management, memory, and session persistence architectures.
- Implement access controls that enforce user permissions and enterprise security requirements.
- Integrate JSON Schema, Protocol Buffers, and identity-based authorization into AI tool execution.
- Develop runtime safeguards to prevent runaway agent execution and cascading failures.
- Implement retry logic, token and cost controls, and deterministic termination conditions.
- Design Human-in-the-Loop approval workflows for sensitive or high-consequence actions.
- Support reliable deployment and operation of secure AI systems.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
