Agentic AI Engineer: LLM Orchestration & RAG

Zohorecruit; Jacksonville (FL); On-site; USD 110,000 - 170,000; Full time

Job summary

Zohorecruit in Jacksonville, FL is seeking an Agentic AI Developer to design, build, and deploy autonomous agent systems that reason over diverse data using modern LLMs and orchestration frameworks. You will work closely with product, data, and ML teams to translate business requirements into intelligent automated workflows.

Responsibilities include building RAG pipelines, integrating multiple data sources, and delivering production-ready Python code.

Qualifications

• 2–5 years of hands-on software development experience post-undergrad.
• Strong Python programming and production ML experience.
• Deep understanding of agentic architectures, LLMs, and orchestration frameworks like Rasa or LangChain.
• Experience with OpenAI, Claude, and LLaMA models.

Responsibilities

• Design and implement autonomous agents leveraging LLMs like GPT-4, LLaMA, Claude and orchestrate them using tools.
• Develop and fine-tune Retrieval-Augmented Generation (RAG) pipelines for context-aware tasks.
• Collaborate with product, data, and ML teams to translate requirements into agentic workflows.
• Integrate multiple data sources into AI pipelines for enhanced reasoning and decision-making.
• Build tools for real-time inference, reasoning, and agent monitoring in production.
• Conduct performance analysis, A/B testing, and continuous improvement of agents.
• Write clean, production-grade Python code and participate in code reviews and architecture decisions.
• Communicate complex technical concepts clearly to technical and non-technical stakeholders.

Skills

Python

LLMs

Agentic architectures

Rasa/LangChain/LangGraph

Tools

Rasa

LangChain

LangGraph

Job description

Zohorecruit in Jacksonville, FL is seeking an Agentic AI Developer to design, build, and deploy autonomous agent systems that reason over diverse data using modern LLMs and orchestration frameworks. You will work closely with product, data, and ML teams to translate business requirements into intelligent automated workflows.

Responsibilities include building RAG pipelines, integrating multiple data sources, and delivering production-ready Python code.