About the role

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.