Artificial Intelligence Engineer

Resource Management Concepts • Charleston, SC

4d • Onsite

About The Position

Resource Management Concepts, Inc. (RMC) is seeking an AI Engineer to design and deploy secure AI systems connecting foundation models with enterprise tools, data, and services. The role involves building agent architectures, advanced retrieval capabilities, and stateful workflows that perform complex tasks while enforcing user permissions and supporting reliable, controlled execution. Candidates should bring hands-on experience with AI orchestration and distributed systems, along with a practical approach to security, observability, and human oversight.

This position is contingent on contract award and position availability. It is a full-time, on-site role at a Government facility in Charleston, South Carolina.

Requirements

• Bachelor’s degree in Cybersecurity, Computer/Electrical/Electronics Engineering, or Mathematics with a computer science concentration, or equivalent.
• Production experience with MCP servers and clients, LangGraph, CrewAI, and Claude Agent SDK; ability to design custom cognitive architectures beyond standard frameworks.
• Expertise in GraphRAG, dynamic query routing, self-correcting retrieval, context compression, state serialization, and session persistence.
• Proficiency in JSON Schema and Protobuf.
• Experience integrating IAM tokens and claims into AI tool execution to enforce zero-trust, per-user data access.
• Experience building fault-tolerant distributed systems with idempotent API/tool mutations, early-exit conditions, automated budget controls, and asynchronous HITL suspension and resumption.
• At least 5 years of relevant professional experience.
• Willingness to work full-time onsite at a Government facility.
• Active TS/SCI clearance and ability to obtain a CI polygraph.

Nice To Haves

• Master’s degree in Cybersecurity, Computer/Electrical/Electronics Engineering, or Mathematics with a computer science concentration, or equivalent.
• Experience with agent trajectory evaluation, step-level tracing using OpenTelemetry, LangSmith, or Arize Phoenix, and automated red-teaming for prompt injection and privilege escalation.
• Experience deploying AI in secure, regulated, or mission-critical environments requiring auditability and data lineage.
• Proficiency in Python and TypeScript or Go for building high-throughput, low-latency MCP servers and custom orchestration runtimes.

Responsibilities

• Architect modular, interoperable agent ecosystems using the Model Context Protocol (MCP) to standardize connections between foundation models, external tools, and enterprise data services.
• Design complex stateful workflows using production orchestration frameworks such as LangGraph, CrewAI, and Claude Agent SDK.
• Engineer advanced retrieval systems, including Graph-based RAG, Agentic Routing, and Corrective RAG (CRAG).
• Design memory architectures that optimize context-window utilization and reliably manage state across long-lived, multi-turn agent sessions.
• Establish strict permission boundaries around autonomous tool calling.
• Map data serialization schemas such as JSON Schema and Protocol Buffers to enterprise ACLs and RBAC/ABAC policies so agents only retrieve data and execute actions authorized for the invoking end user.
• Build resilient execution harnesses to prevent runaway agent loops and cascading failures.
• Implement idempotent tool retries, strict token and cost budgets, deterministic early-exit stop conditions, and Human-in-the-Loop (HITL) approval gates for high-consequence actions.

Benefits

• Career growth and employee investment through training, certification, and education.
• Tuition assistance and certifications.
• Competitive paid vacation package with 11 paid federal holidays.
• High-quality, low-deductible healthcare plans.
• Pet insurance.
• Competitive 401K package.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior