Agentic AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Agentic AI Engineer, a 6-month contract position with a pay rate of "negotiable." The role requires on-site work, expertise in Google Vertex AI, LangChain, and GCP, and experience in deploying scalable AI systems.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 19, 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
Auburn Hills, MI
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🧠 - Skills detailed
#NLP (Natural Language Processing) #AI (Artificial Intelligence) #Databases #Langchain #GCP (Google Cloud Platform) #Monitoring #Deployment #Scala
Role description
Must come and work on-site from Day 1.
Skills
Key Responsibilities
• Design and implement agentic AI architectures using Google Vertex AI models (Gemini, PaLM, Codey)
• Develop and deploy AI agents using LangChain and Model Context Protocol (MCP) architectures
• Build scalable, production-ready AI systems leveraging GCP services including Vertex AI Pipelines, Matching Engine, and AI Platform Implement multi-agent systems with complex reasoning, planning, and tool-use capabilities
• Design and optimize vector databases and embedding systems for retrieval-augmented generation (RAG)
• Integrate agents with external APIs, databases, and enterprise systems
• Establish MLOps practices for agent deployment, monitoring, and continuous improvement
staffing@techjordan.com
#generativeai #airchitect #LLM #GCP #NLP #deeplearning
Must come and work on-site from Day 1.
Skills
Key Responsibilities
• Design and implement agentic AI architectures using Google Vertex AI models (Gemini, PaLM, Codey)
• Develop and deploy AI agents using LangChain and Model Context Protocol (MCP) architectures
• Build scalable, production-ready AI systems leveraging GCP services including Vertex AI Pipelines, Matching Engine, and AI Platform Implement multi-agent systems with complex reasoning, planning, and tool-use capabilities
• Design and optimize vector databases and embedding systems for retrieval-augmented generation (RAG)
• Integrate agents with external APIs, databases, and enterprise systems
• Establish MLOps practices for agent deployment, monitoring, and continuous improvement
staffing@techjordan.com
#generativeai #airchitect #LLM #GCP #NLP #deeplearning
