Onsite Agentic AI Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Onsite Agentic AI Lead in NYC, offering a contract position. Requires 1-2 years in AI/LLM systems design, 5+ years in AI/ML architecture, and expertise in Python, agentic AI frameworks, and cloud-native architecture (AWS).
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 20, 2025
🕒 - Project duration
Unknown
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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
New York, NY
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🧠 - Skills detailed
#Security #Compliance #Python #Logging #API (Application Programming Interface) #Base #ML (Machine Learning) #Databases #Deployment #Observability #Monitoring #AWS (Amazon Web Services) #Cloud #AI (Artificial Intelligence)
Role description
Onsite Agentic AI Lead
Location : (NYC), NY
Type : Contract
Hands On:
• Agentic AI frameworks (LangGraph, AutoGen, CrewAI)
• Python (core language, API integration, prompt design)
• LLMs and tool/function calling
• RAG pipelines and knowledge base integration
• Designing agent workflows and reusable templates
• Vector databases (FAISS, Chroma, Pinecone, etc)
• Observability stack setup (logging, drift/bias monitoring)
Knowledge of:
• Agent Development Lifecycle (ADLC)
• Governance and compliance for AI systems (privacy, safety, auditability)
• Security and risk checklists in AI deployments
• Cloud-native architecture (AWS)
Experience:
• 1-2 years designing and deploying AI/LLM systems in production
• 5+ years in AI/ML systems architecture
Onsite Agentic AI Lead
Location : (NYC), NY
Type : Contract
Hands On:
• Agentic AI frameworks (LangGraph, AutoGen, CrewAI)
• Python (core language, API integration, prompt design)
• LLMs and tool/function calling
• RAG pipelines and knowledge base integration
• Designing agent workflows and reusable templates
• Vector databases (FAISS, Chroma, Pinecone, etc)
• Observability stack setup (logging, drift/bias monitoring)
Knowledge of:
• Agent Development Lifecycle (ADLC)
• Governance and compliance for AI systems (privacy, safety, auditability)
• Security and risk checklists in AI deployments
• Cloud-native architecture (AWS)
Experience:
• 1-2 years designing and deploying AI/LLM systems in production
• 5+ years in AI/ML systems architecture
