

Crossing Hurdles
Data Engineer – AI | Remote
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer – AI, offering $250K - $600K/year for a full-time, remote position. Key skills include Python, LLMs, RAG, and cloud services (AWS GovCloud, Azure IL5+). Experience in data pipelines and ETL processes is required. Expected duration is over 6 months.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
2727
-
🗓️ - Date
June 10, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Azure #Data Pipeline #Langchain #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #AWS (Amazon Web Services) #Metadata #Python #REST API #Security #Data Catalog #ML (Machine Learning) #DevOps #Cloud #Data Engineering #REST (Representational State Transfer)
Role description
Position: Data Engineer AI
Type: Full-Time
Compensation: $250K - $600K/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: $250K - $600K/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






