GenAI and Agentic AI Specialist W2 Contract
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a "GenAI and Agentic AI Specialist" on a W2 contract for 3+ months, remote. Key skills include experience in AI-driven systems, end-to-end ML lifecycle, GenAI, LLM fine-tuning, and Agentic AI methodologies.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 3, 2025
🕒 - Project duration
3 to 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#ML (Machine Learning) #Knowledge Graph #AI (Artificial Intelligence)
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Nasscomm, Inc., is seeking the following. Apply via Dice today!
Position: - GenAI and Agentic AI Specialist
Location: - Remote
Duration: - 3+ Months contract
•
• W2 ONLY
•
• Description: -
GenAI and Agentic AI
Strong experience in designing, developing, integrating, deploying, and maintaining sophisticated AI-driven systems at scale.
Experience in end-to-end ML solutions lifecycle (explore, design, model, train, optimize, deploy, monitor, and measure).
Experience with GenAI, LLM fine-tuning and integration, RAG enablement, Prompt engineering and Knowledge Graphs
Experience with Agentic AI guidance, adding guardrails, human in the loop, multi-agent workflows, reflection, citing sources, response verification, and other methodologies to increase the accuracy of agentic responses and prevent hallucinations
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Nasscomm, Inc., is seeking the following. Apply via Dice today!
Position: - GenAI and Agentic AI Specialist
Location: - Remote
Duration: - 3+ Months contract
•
• W2 ONLY
•
• Description: -
GenAI and Agentic AI
Strong experience in designing, developing, integrating, deploying, and maintaining sophisticated AI-driven systems at scale.
Experience in end-to-end ML solutions lifecycle (explore, design, model, train, optimize, deploy, monitor, and measure).
Experience with GenAI, LLM fine-tuning and integration, RAG enablement, Prompt engineering and Knowledge Graphs
Experience with Agentic AI guidance, adding guardrails, human in the loop, multi-agent workflows, reflection, citing sources, response verification, and other methodologies to increase the accuracy of agentic responses and prevent hallucinations
