HireKul
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" with a pay rate of "unknown." Key skills include Azure, AI, automation, and deployment, requiring proven experience in deploying AI solutions into production.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 9, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
New Jersey, United States
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🧠 - Skills detailed
#Deployment #Azure #Automation #AI (Artificial Intelligence)
Role description
About the Role:
We are building a focused AI capability to drive automation and smarter decision-making—and we are looking for someone who can build and deploy real solutions, not just experiment.
What You Will Do:
• Design and deploy AI solutions end-to-end
• Build workflows using LLMs (GPT, Claude), Azure OpenAI, and Copilot
• Integrate AI into business tools and processes
• Work directly with stakeholders to deliver solutions
• Ship production-ready tools with measurable impact
What We Are Looking For:
• Proven experience deploying AI into production
• Strong workflow thinking (input → model → output → user adoption)
• Hands-on experience with LLMs, automation, and AI workflows.
• Ability to own delivery end-to-end including scoping, design, building, testing and deployment in AI environment.
About the Role:
We are building a focused AI capability to drive automation and smarter decision-making—and we are looking for someone who can build and deploy real solutions, not just experiment.
What You Will Do:
• Design and deploy AI solutions end-to-end
• Build workflows using LLMs (GPT, Claude), Azure OpenAI, and Copilot
• Integrate AI into business tools and processes
• Work directly with stakeholders to deliver solutions
• Ship production-ready tools with measurable impact
What We Are Looking For:
• Proven experience deploying AI into production
• Strong workflow thinking (input → model → output → user adoption)
• Hands-on experience with LLMs, automation, and AI workflows.
• Ability to own delivery end-to-end including scoping, design, building, testing and deployment in AI environment.
