Agentic AI Architect Location: Charlotte, NC – Remote Job Type: Contract

Agentic AI Architect

Location: Charlotte, NC – Remote
Job Type: Contract

Job Description

We are seeking an experienced Agentic AI Architect to design, develop, and implement advanced AI solutions powered by Generative AI, Large Language Models (LLMs), and autonomous AI agents. The ideal candidate will have strong hands-on experience in agentic AI architecture, multi-agent systems, RAG, LLM orchestration, and enterprise AI solution design.

The candidate will work closely with business stakeholders, data engineers, software developers, and enterprise architecture teams to build scalable, secure, and production-ready AI applications that automate complex business processes.

Key Responsibilities

Design and implement Agentic AI architectures using autonomous agents, multi-agent collaboration, and goal-oriented AI workflows.
Develop AI agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies.
Design and implement Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, and enterprise knowledge sources.
Integrate LLMs with enterprise applications, APIs, databases, and external tools to enable intelligent automation and decision-making.
Develop agent orchestration, planning, reasoning, memory management, tool calling, and workflow execution capabilities.
Design scalable AI architectures leveraging Python, REST APIs, microservices, and cloud platforms.
Implement Model Context Protocol (MCP) and tool integrations where applicable to enable agents to interact with enterprise systems.
Establish AI security, governance, access controls, guardrails, observability, and responsible AI practices.
Optimize AI solutions for performance, scalability, reliability, latency, and cost efficiency.
Collaborate with cross-functional teams to translate business requirements into enterprise-grade AI solutions.
Lead technical design discussions, architecture reviews, proof of concepts, and production deployments.
Establish best practices for AI evaluation, testing, monitoring, and continuous improvement.
Required Skills

Strong experience in AI Architecture, Agentic AI, and Generative AI solution development.
Hands-on programming experience with Python and AI application development.
Experience with LLMs, including OpenAI, Anthropic Claude, Google Gemini, or similar models.
Strong knowledge of AI agent frameworks, such as LangGraph, LangChain, AutoGen, or CrewAI.
Experience building multi-agent systems, autonomous workflows, and AI-powered automation solutions.
Expertise in RAG, embeddings, vector databases, semantic search, and knowledge retrieval.
Experience with REST APIs, microservices, API integrations, and enterprise application connectivity.
Understanding of prompt engineering, context management, function calling, and structured outputs.
Experience with cloud-based AI services on AWS, Azure, or Google Cloud Platform (GCP).
Knowledge of AI security, governance, evaluation frameworks, and production deployment practices.
Strong communication, solution design, and technical leadership skills.
Preferred Qualifications

Experience implementing Model Context Protocol (MCP) and agent-to-tool integrations.
Familiarity with vector databases such as Pinecone, Weaviate, Milvus, or Chroma.
Experience with Docker, Kubernetes, CI/CD, and MLOps/LLMOps.
Knowledge of agent evaluation, observability, hallucination mitigation, and responsible AI.
Experience integrating AI agents with enterprise data platforms and business applications.
Previous experience leading enterprise AI architecture initiatives from proof of concept through production.
Ideal Candidate Profile

The ideal candidate is a hands-on Agentic AI Architect who can design enterprise AI solutions, build intelligent agents, orchestrate multi-agent workflows, integrate LLMs with enterprise systems, and guide solutions into production.

Key Search Keywords: Agentic AI Architect, Generative AI, AI Agents, Multi-Agent Systems, LangGraph, LangChain, MCP, RAG, LLM, Python, Vector Database, AI Orchestration, Enterprise AI Architecture.