TalentBridge

Artificial Intelligence Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer (AI Lead) on a 12+ month remote contract, open to U.S. Citizens or Green Card Holders. Requires expertise in RAG, agentic AI, multimodal systems, and strong Python skills.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 19, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Knowledge Graph #Monitoring #Scala #Indexing #Observability #AI (Artificial Intelligence) #Leadership #Python
Role description
AI Lead Remote 12+ Months of contract ✅ Work Eligibility • This role is open only to candidates who are U.S. Citizens or Green Card Holders. • W2 candidates only. (No C2C / No third-party vendors) Overview Seeking an AI Lead to drive enterprise-grade AI solutions with expertise in RAG, agentic AI, multimodal systems, and large-scale knowledge management. This role focuses on end-to-end solution delivery, innovation, and technical leadership. Key Responsibilities • Architect and deliver complex RAG solutions across multiple domains with large (TB-scale) knowledge bases. • Define chunking, retrieval, and vector store strategies for high-quality results. • Build agentic AI systems capable of autonomous planning, decisioning, and tool usage. • Lead multimodal experiments using text, images, diagrams, and structured data. • Implement knowledge graphs to enhance reasoning and domain understanding. • Drive LLM-based solutions using strong prompt engineering and OpenAI expertise. • Establish AI evals, observability, and monitoring frameworks. • Provide industry insights and propose alternate AI solution approaches. • Lead and guide engineering teams in Python-based and LLM-driven development. Skills & Experience • Hands-on experience with RAG, vector stores, embeddings, and indexing. • Strong background in OpenAI, prompt engineering, and LLM orchestration. • Experience with agentic AI frameworks, workflow orchestration, and tool calling. • Knowledge of knowledge graphs and multimodal AI use cases. • Proficiency in Python and building scalable AI services. • Understanding of AI evals, observability, monitoring, and quality frameworks.