Agentic AI Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an "Agentic AI Developer" in San Jose, CA, lasting 6+ months, with a pay rate of "TBD." Requires 5+ years of experience in agentic AI frameworks, machine learning, and LLMs, plus skills in TensorFlow and PyTorch.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 19, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
San Jose, CA
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🧠 - Skills detailed
#ML (Machine Learning) #TensorFlow #PyTorch #AI (Artificial Intelligence) #Langchain #Scala
Role description
Title - Agentic AI Development Consultant
Location - San Jose, CA
Duration - 6+ Months
Key Responsibilities
• 5+ years of experience
• Hands on development using agentic AI frameworks such as LangGraph, LangChain, and other orchestration tools to build scalable agent based systems.
• Design and implement tool based workflows and integrations within the agentic AI ecosystem to support modular and reusable components.
• Develop and integrate with MCP clients to support external orchestration and control flows.
• Build and maintain conversational AI bots with contextual understanding, memory, and dynamic tool invocation.
• Demonstrate expert level understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit learn) and how they integrate into agentic systems for inference, training, or feedback loops.
• Deep understanding of how LLMs are leveraged within agentic AI, including state management, handoffs between agents/tools, and interaction patterns in multi agent workflows.
• Apply LLM Ops practices, including prompt engi
Title - Agentic AI Development Consultant
Location - San Jose, CA
Duration - 6+ Months
Key Responsibilities
• 5+ years of experience
• Hands on development using agentic AI frameworks such as LangGraph, LangChain, and other orchestration tools to build scalable agent based systems.
• Design and implement tool based workflows and integrations within the agentic AI ecosystem to support modular and reusable components.
• Develop and integrate with MCP clients to support external orchestration and control flows.
• Build and maintain conversational AI bots with contextual understanding, memory, and dynamic tool invocation.
• Demonstrate expert level understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit learn) and how they integrate into agentic systems for inference, training, or feedback loops.
• Deep understanding of how LLMs are leveraged within agentic AI, including state management, handoffs between agents/tools, and interaction patterns in multi agent workflows.
• Apply LLM Ops practices, including prompt engi
