

Crossing Hurdles
Data Engineer – AI | Remote
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Engineer – AI position, remote, with a contract length of over 6 months and a pay rate of $200K - $350K/year. Key skills required include Python, LLMs, RAG systems, and cloud AI services expertise.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
1590
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🗓️ - Date
July 9, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
-
🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Python #Data Catalog #REST (Representational State Transfer) #Security #Langchain #Azure #REST API #DevOps #Data Pipeline #ML (Machine Learning) #Metadata #Data Engineering #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Cloud
Role description
Position: Data Engineer AI
Type: Full-Time
Compensation: $200K - $350K/yr
Location: Remote
Role Responsibilities
• Design, implement, and optimize AI/ML models using large language models (LLMs), retrieval-augmented generation (RAG), and prompt engineering for production-grade applications.
• Develop and orchestrate multi-agent systems utilizing frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, adhering to secure coding and DevOps best practices.
Requirements
• Have strong relevant experience in Python for AI/ML development, including proficiency with REST APIs and SDK integration.
• Have hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
• Be familiar with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
• Possess a deep understanding of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Have a background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
Application Process
• Easy Apply on LinkedIn
• Check email for next steps
• Participate in resume evaluation & interview stage
Position: Data Engineer AI
Type: Full-Time
Compensation: $200K - $350K/yr
Location: Remote
Role Responsibilities
• Design, implement, and optimize AI/ML models using large language models (LLMs), retrieval-augmented generation (RAG), and prompt engineering for production-grade applications.
• Develop and orchestrate multi-agent systems utilizing frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, adhering to secure coding and DevOps best practices.
Requirements
• Have strong relevant experience in Python for AI/ML development, including proficiency with REST APIs and SDK integration.
• Have hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
• Be familiar with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
• Possess a deep understanding of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Have a background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
Application Process
• Easy Apply on LinkedIn
• Check email for next steps
• Participate in resume evaluation & interview stage






