AI Engineer

We are seeking a highly skilled AI Engineer to design, develop, and deploy advanced AI/ML systems focused on next-generation agentic AI solutions powered by retrieval-augmented generation (RAG). This role leverages modern orchestration frameworks such as LangGraph and Model Context Protocol (MCP) and requires deep expertise in Python-based AI development, end-to-end RAG architectures, and Model Risk Management (MRM). Location: Charlotte, North Carolina. Job type: Contract.

About the role

The ideal candidate will have hands-on experience designing agent systems capable of reasoning, planning, tool usage, and executing complex multi-step workflows. A strong foundation in RAG architectures, including Graph RAG, is required. The role demands experience in Model Risk Management (MRM) to ensure AI systems are governed, explainable, auditable, and aligned with enterprise risk, compliance, and regulatory standards. The candidate will play a critical role in building production-grade AI systems that are both innovative and trustworthy.

Responsibilities

• Design and implement advanced RAG pipelines using vector databases, embeddings, knowledge graphs, and hybrid retrieval strategies.
• Develop agentic AI systems using LangGraph, enabling dynamic task planning, reasoning, tool orchestration, and multi-agent workflows.
• Integrate Model Context Protocol (MCP) for standardized context sharing, tool interoperability, and scalable agent communication.
• Design memory systems and contextual state management for agent continuity and long-running workflows.
• Implement evaluation pipelines, prompt engineering strategies, and guardrails to ensure performance, safety, and reliability.
• Apply Model Risk Management (MRM) practices across the AI lifecycle, including model validation, explainability, bias detection, monitoring, and documentation.

Requirements

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong proficiency in Python programming, with experience building scalable AI/ML systems.
• Hands-on experience with agentic AI frameworks, particularly LangGraph, and emerging standards such as Model Context Protocol (MCP).
• Strong experience designing and implementing advanced RAG architectures, including Graph RAG.
• Experience with LLM orchestration frameworks such as LangChain, LangGraph, and LlamaIndex.
• Proven experience deploying LLM-powered production systems.
• Strong experience with Python ML/AI frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search) and semantic retrieval systems.
• Deep understanding of agent orchestration patterns, including planning, reflection, tool usage, and multi-agent collaboration.
• Experience implementing Graph RAG using knowledge graphs and structured data integration.
• Expertise in memory architectures (short-term, long-term, episodic memory) in agent systems.
• Strong understanding of LLMOps/MLOps, including CI/CD, observability, monitoring, and performance optimization.
• Working knowledge of Model Risk Management (MRM) frameworks including governance, validation, and lifecycle controls.
• Familiarity with AI safety and alignment techniques, including guardrails, human-in-the-loop systems, and bias mitigation.
• Experience with model evaluation, benchmarking, and explainability tools.
• Proficiency with development tools such as GitHub, VS Code, JIRA, and modern engineering workflows.

Pay

$51.59 - 61.59 per hour

Schedule

8am to 5pm

Benefits

• Comprehensive benefits package, including medical, prescription, dental, vision, AD&D, and life insurance offerings.
• Short-term disability coverage.
• 401K plan (all benefits are based on eligibility).