Data Engineer (Azure AI Foundry)

Job Summary


Responsibilities

• AI Architecture Agentic Deployment: Design, develop, and deploy production-grade AI applications and intelligent agents using Azure AI Foundry, enabling scalable, secure, and fully governed enterprise AI solutions.
• Data Foundations Modernization: Architect high-performance data models and automated pipelines using Azure Databricks, Python, and Apache Spark. Modernize legacy systems and execute advanced performance tuning on Spark clusters.
• LLMs Prompt Engineering: Apply advanced prompt engineering techniques, fine-tune LLM workflows, and manage enterprise AI integrations across complex business environments.
• Technical Leadership Mentoring: Act as the primary Subject Matter Expert (SME), designing end-to-end architectures, mentoring junior engineers, and actively contributing to guilds.
• Strategic Stakeholder Management: Translate data and AI strategy into robust IT solutions. Present findings, metrics, and architectures directly to technical teams and business leaders to drive adoption.
• Operations Change Governance: Oversee incident, problem, and change management processes for production AI and data workflows to ensure high availability, speed of delivery, and cost efficiency.

Requirements

• 6+ years of high-impact engineering experience on architecting, building, and deploying LLM applications, custom agents, and governed AI solutions on Azure AI Foundry.
• Deep proficiency in Python for both data pipeline engineering and custom AI development.
• Advanced technical expertise in Azure Databricks, including PySpark, cluster optimization, and modern lakehouse design.
• Strong foundation in SQL, high-volume ETL/ELT pipeline design, and data modeling frameworks.
• Deep knowledge of prompt engineering, LLM orchestration, evaluation frameworks, and guardrails within Azure ecosystems.
• Outstanding communication skills with a proven track record of influencing both technical teams and non-technical business stakeholders.

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