AI Engineer – Agentic AI / Generative AI

TALENT Software Services; Louisville (KY); On-site; USD 165,000 - 248,000; Full time

Job summary

TALENT Software Services in Louisville, KY is seeking an AI Engineer to lead agentic AI initiatives, building full‑stack, production‑ready GenAI solutions with RAG and multi‑agent orchestration capabilities.

The role focuses on deploying AI applications using Python, LangChain, and LangSmith, with emphasis on graph databases like Neo4j and scalable end‑to‑end delivery in a 6‑month contract.

Qualifications

• Strong experience in Agentic AI full‑stack development.
• Hands-on experience with Retrieval-Augmented Generation (RAG).
• Experience with Model Context Protocol (MCP).
• Strong experience in multi‑agent orchestration.
• Experience with end-to-end AI solution deployment.
• Strong hands-on experience with LangChain.
• Experience with LangSmith.
• Strong Python programming skills.
• Experience with Graph Databases such as Neo4j.

Responsibilities

• Design and develop Agentic AI full‑stack solutions.
• Build production‑ready RAG‑based applications.
• Design and implement multi‑agent architectures and orchestration frameworks.
• Implement MCP‑based integrations for AI agents and tools.
• Develop AI applications using Python.
• Build conversational and intelligent applications using LangChain.
• Use LangSmith for LLM app development, tracing, evaluation and monitoring.
• Design and implement graph‑based solutions using Neo4j or similar.

Skills

Agentic AI Full Stack

RAG

MCP

Multi-Agent orchestration

Python

LangChain

LangSmith

Graph Databases

Neo4j

End-to-End Deployment

AI Engineering

GCP experience

Tools

LangChain

LangSmith

Neo4j

GCP

Job description

• Job Title: AI Engineer - Agentic AI / Generative AI
• Location: Louisville, KY
• Duration: 6 months
• Experience Required: 8-10 years
• Primary Focus: Agentic AI, RAG, MCP, Multi-Agent Orchestration, Python, LangChain, LangSmith, and Graph Databases
• Keyword: AI and Automation

Job Description - AI Engineer

• Job Title: AI Engineer - Agentic AI / Generative AI
• Location: Louisville, KY
• Duration: 6 months
• Experience Required: 8-10 years
• Role: AI Engineer
• Essential Skill: AI Engineering
• Primary Focus: Agentic AI, RAG, MCP, Multi-Agent Orchestration, Python, LangChain, LangSmith, and Graph Databases
• Desirable Skill: Google Cloud Platform (GCP)
• Keyword: AI and Automation

Must-Have Technical Skills

• Strong experience in Agentic AI Full Stack development.
• Hands-on experience with Retrieval-Augmented Generation (RAG).
• Experience with Model Context Protocol (MCP).
• Strong experience in Multi-Agent orchestration.
• Experience with end-to-end AI solution deployment.
• Strong hands-on experience with LangChain.
• Experience with LangSmith.
• Strong Python programming skills.
• Experience with Graph Databases, such as:
• Neo4j
• Other graph database technologies
• Experience building scalable AI/GenAI applications from development through production deployment.

Good-to-Have Skills

• Google Cloud Platform (GCP) experience.
• Generative AI application development.
• AI/ML platform and cloud deployment experience.
• Experience with enterprise AI and automation solutions.

Roles & Responsibilities

• Design and develop Agentic AI full-stack solutions.
• Build production-ready RAG-based applications.
• Design and implement multi-agent architectures and orchestration frameworks.
• Implement MCP-based integrations for AI agents and tools.
• Develop AI applications using Python.
• Build conversational and intelligent applications using LangChain.
• Use LangSmith for LLM application development, tracing, evaluation, and monitoring.
• Design and implement graph-based solutions using Neo4j or similar graph databases.
• Develop AI solutions that integrate LLMs, enterprise data, APIs, tools, and external systems.
• Manage end-to-end deployment of AI applications from development through production.
• Design scalable and reliable AI application architectures.
• Integrate RAG pipelines with enterprise knowledge sources and data repositories.
• Develop agent workflows capable of reasoning, tool usage, task execution, and multi-agent collaboration.
• Troubleshoot and optimize AI application performance, reliability, and scalability.
• Collaborate with engineering and business teams to translate requirements into AI-driven solutions.
• Follow software engineering, testing, deployment, and monitoring best practices.
• Leverage GCP for AI application development and deployment where applicable.

Key Skills / Keywords

• Agentic AI
• Generative AI
• AI Engineering
• AI Automation
• RAG
• Retrieval-Augmented Generation
• MCP
• Model Context Protocol
• Multi-Agent Systems
• Multi-Agent Orchestration
• LangChain
• LangSmith
• Python
• Neo4j
• Graph Database
• LLM
• LLM Application Development
• AI Full Stack
• End-to-End Deployment
• GCP
• Google Cloud
• AI Architecture
• AI/ML Integration