Agentic AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Agentic AI Engineer on a long-term contract, hybrid in Tampa FL, Dallas TX, or Basking Ridge NJ. Key skills include LangGraph, Python, and GCP. Experience in architecting multi-agent AI systems is required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
-
🗓️ - Date discovered
September 27, 2025
🕒 - Project duration
Unknown
-
🏝️ - Location type
Hybrid
-
📄 - Contract type
Unknown
-
🔒 - Security clearance
Unknown
-
📍 - Location detailed
Tampa, FL
-
🧠 - Skills detailed
#Neo4J #AI (Artificial Intelligence) #Knowledge Graph #GCP (Google Cloud Platform) #React #Python #Databases #Langchain #Reinforcement Learning #Automation #Scala
Role description
Role : Agentic AI Engineer
Location : Tampa FL, Dallas TX, or Basking Ridge NJ – (3days Hybrid)
Duration : Long Term Contract
Primary - LangGraph, ReAct, LangChain, LlamaIndex, Python
Secondary - GCP, Google Spanner/Neo4j, CrewAI, AutoGen, OpenAI
Key Responsibilities:
Architecting & Scaling Agentic AI Solutions
· Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving.
· Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains.
· Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications.
Hands-On Development & Optimization
· Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability.
· Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning.
· Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making.
Role : Agentic AI Engineer
Location : Tampa FL, Dallas TX, or Basking Ridge NJ – (3days Hybrid)
Duration : Long Term Contract
Primary - LangGraph, ReAct, LangChain, LlamaIndex, Python
Secondary - GCP, Google Spanner/Neo4j, CrewAI, AutoGen, OpenAI
Key Responsibilities:
Architecting & Scaling Agentic AI Solutions
· Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving.
· Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains.
· Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications.
Hands-On Development & Optimization
· Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability.
· Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning.
· Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making.
