Azure AI Engineer

Job Overview

Our client is seeking an Azure AI Engineer to design develop deploy and support enterprise-grade AI solutions that address business challenges through modern cloud technologies. This role focuses on building scalable AI applications integrating intelligent capabilities into existing platforms and ensuring reliable deployment in production environments.

Working closely with cross-functional engineering data and product teams the successful candidate will help deliver robust AI solutions while maintaining high standards for performance security governance and Responsible AI practices.


Key Responsibilities

• Design develop and deploy production-ready AI models and end-to-end AI solutions.
  
• Build and integrate AI capabilities into enterprise applications using APIs and cloud-based architectures.
  
• Partner with software engineers data engineers and product teams to deliver scalable and well-integrated AI solutions.
  
• Monitor evaluate and continuously improve model performance reliability scalability and accuracy in production.
  
• Develop and maintain prompt orchestration workflows AI pipelines and agent-based solutions.
  
• Implement Retrieval-Augmented Generation (RAG) architectures including embedding generation indexing strategies and context retrieval.
  
• Promote Responsible AI practices by ensuring compliance with governance security and ethical AI standards.
  
• Establish monitoring logging and observability processes for AI applications to support operational excellence.
  
• Apply secure-by-design principles including identity management access controls and data protection measures.
  
• Translate business requirements into practical AI solutions by defining success metrics performance indicators and operational guardrails.
  

Qualifications
Experience

• 36 years of professional experience in AI/ML engineering software engineering or cloud-based AI solution development.
  
• Hands-on experience building deploying and supporting AI or large language model (LLM) applications in production environments.
  
• Experience working with Microsoft Azure or comparable cloud platforms such as AWS or Google Cloud Platform.
  
• Practical experience in prompt engineering AI orchestration or Retrieval-Augmented Generation (RAG) implementations.
  
• Experience collaborating with cross-functional engineering and product teams throughout the software development lifecycle.
  

Technical Knowledge
Candidates should possess strong knowledge in the following areas:

• AI and LLM engineering including prompt engineering workflow orchestration agent-based AI and RAG solutions.
  
• Software development using Python REST APIs JSON microservices and CI/CD methodologies.
  
• Azure AI services including model deployment inference APIs AI development platforms and cloud cost optimization.
  
• Data retrieval techniques such as embeddings chunking strategies vector search and hybrid search implementations.
  
• Cloud infrastructure identity and access management observability networking and secure cloud architectures.
  
• Responsible AI principles including model governance explainability policy compliance and AI safety.
  
• Low-code AI integration using Microsoft Power Platform and Copilot-based extensibility.
  

Skills

• Ability to translate business needs into scalable AI-driven solutions.
  
• Strong communication skills with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
  
• Excellent analytical thinking and problem-solving skills particularly in complex or evolving environments.
  
• Effective collaboration across engineering product and data teams.
  
• Ability to establish measurable success criteria performance metrics and governance controls for AI solutions.