Talent Groups
Artificial Intelligence Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer, offering a contract length of "unknown" and a pay rate of "unknown." Key skills required include Python, REST, cloud platforms (Snowflake, Databricks), and experience in MLOps/AIOps.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 19, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Jersey City, NJ
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🧠 - Skills detailed
#Cloud #Deployment #Monitoring #Python #Scala #Microservices #AI (Artificial Intelligence) #Snowflake #Automation #Databricks #REST (Representational State Transfer)
Role description
We are looking for an experienced Senior AI Platform Engineer to design, develop, and scale next-generation AI-driven platforms that power intelligent automation and advanced enterprise solutions.
Key Responsibilities
• Design and develop AI-driven autonomous systems and multi-agent architectures using modern agentic frameworks and cognitive computing technologies.
• Build and optimize high-performance backend services using Python-based microservices architecture, including scalable REST and gRPC APIs.
• Develop and manage end-to-end MLOps/AIOps pipelines, automating model testing, deployment, monitoring, and lifecycle management.
• Architect and maintain scalable data infrastructure and pipelines across modern cloud data platforms including Snowflake, Databricks, and Lakehouse environments.
• Collaborate with engineering teams to deliver scalable, reliable, and production-ready AI solutions aligned with enterprise architecture standards.
We are looking for an experienced Senior AI Platform Engineer to design, develop, and scale next-generation AI-driven platforms that power intelligent automation and advanced enterprise solutions.
Key Responsibilities
• Design and develop AI-driven autonomous systems and multi-agent architectures using modern agentic frameworks and cognitive computing technologies.
• Build and optimize high-performance backend services using Python-based microservices architecture, including scalable REST and gRPC APIs.
• Develop and manage end-to-end MLOps/AIOps pipelines, automating model testing, deployment, monitoring, and lifecycle management.
• Architect and maintain scalable data infrastructure and pipelines across modern cloud data platforms including Snowflake, Databricks, and Lakehouse environments.
• Collaborate with engineering teams to deliver scalable, reliable, and production-ready AI solutions aligned with enterprise architecture standards.
