AI Development Specialist; Azure R

Job Overview

The AI Development Specialist will lead the design, development, and deployment of scalable, production-grade AI solutions on Microsoft Azure. This role owns end-to-end delivery—from data ingestion and model development to deployment and operationalization—ensuring solutions are secure, reliable, cost-effective, and compliant with enterprise standards.

• Design, develop, and deploy end-to-end AI solutions on Azure.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines and prompt strategies.
• Translate business requirements into scalable AI architectures and technical designs.
• Implement event-driven and real-time data integrations using Azure services.
• Containerize applications and manage deployments across AKS, Functions, and App Service.
• Build and maintain CI/CD pipelines for automated testing and releases.
• Apply Infrastructure as Code (IaC) for consistent and repeatable deployments.
• Establish MLOps practices including model versioning, monitoring, and lifecycle management.
• Implement logging, telemetry, and observability for production systems.
• Optimize model performance, scalability, and cost efficiency.
• Ensure adherence to security, data governance, and Responsible AI standards.
• Troubleshoot and resolve production issues across AI and data pipelines.
• Collaborate with data, engineering, and business teams to deliver solutions.
• Produce and maintain technical documentation, architecture diagrams, and runbooks.
• Stay current with emerging AI and Azure technologies and recommend improvements.

• 7+ years of experience in software engineering and/or machine learning engineering.
• Minimum 3+ years delivering production AI solutions on Microsoft Azure.
• Proven track record of deployed solutions, including architecture documentation and operational runbooks.
• Strong experience in:
  • RAG system design
  • Prompt engineering
  • Performance tuning and optimization
• Solid data engineering background and experience with secure integration patterns.
• Working knowledge of Responsible AI frameworks and regulatory compliance.