AI Data Engineer

Job Summary:

The AI Data Engineer will play a pivotal role in designing and implementing advanced agentic AI systems that leverage cutting-edge GPT-based models. In this dynamic role, you will focus on workflow automation, reasoning capabilities, and orchestration to enhance organizational efficiency and innovation.

Key Responsibilities:

• Design and deploy agentic AI systems using GPT models, emphasizing workflow automation and optimization.
• Create and manage complex multi-agent orchestration pipelines utilizing LangGraph for scalable AI deployments.
• Integrate end-to-end data solutions using Fabric, Azure Databricks, and Snowflake to facilitate robust ETL/ELT processes.
• Develop and maintain APIs and software integrations to support enterprise-grade applications seamlessly.
• Collaborate with cross-functional teams to identify AI-driven solutions that address business challenges and enhance operational efficiency.
• Conduct performance tuning and troubleshooting of AI systems to ensure optimal functionality and reliability.
• Stay abreast of industry trends and emerging technologies to continually improve AI deployment strategies.

Requirements:

• Proven experience in designing and deploying agentic AI applications, specifically using GPT-based models.
• Strong proficiency in workflow automation and orchestration methodologies, particularly with LangGraph.
• Demonstrated expertise in data engineering, including experience with Fabric, Azure Databricks, and Snowflake.
• Advanced programming skills in Python and PySpark, with a solid understanding of API development and integration.
• Excellent problem-solving and analytical skills, with a keen attention to detail.
• Ability to work independently and collaboratively in fast-paced, agile environments.
• Bachelor's degree in Computer Science, Data Science, or a related field (Master's preferred).

Preferred Qualifications:

• Experience in deploying AI solutions in a cloud-based environment, particularly on Azure.
• Familiarity with machine learning frameworks and libraries, such as TensorFlow or PyTorch.
• Knowledge of advanced analytics techniques and their application in real-world scenarios.
• Previous experience in leading AI-driven projects or teams effectively.
• Certifications related to AI, cloud integration, or data engineering are a plus.