AI Engineer

Role overview

Design, build, and operate enterprise AI and machine learning solutions using Microsoft cloud technologies. The work spans generative AI applications, scalable platforms, and the operational practices needed to deploy, monitor, and govern production services. This is a fixed-term engagement from January 1 to June 15, 2027.

Responsibilities - Develop and support enterprise AI, machine learning, and advanced analytics solutions. - Build applications using Azure AI Services, Azure OpenAI, Azure Machine Learning, and related Microsoft tools. - Implement generative AI capabilities such as LLMs, prompt engineering, retrieval-augmented generation, semantic search, and vector search. - Design cloud-native AI platforms with Azure and Microsoft Fabric, and develop Python applications, APIs, and REST services. - Establish MLOps and LLMOps practices for deployment pipelines, lifecycle management, monitoring, testing, and ongoing improvement. - Integrate AI into business applications, following architecture, security, governance, compliance, risk, and Responsible AI requirements.

Requirements - At least five years delivering AI, machine learning, advanced analytics, data science, or related technology solutions. - Strong experience with Azure AI services, Azure OpenAI, Azure Machine Learning, Microsoft Fabric, and cloud-native architecture. - Practical experience building generative AI and LLM applications, including RAG, prompting, semantic search, and vector search. - Background in AI solution architecture, machine learning engineering, model development, agentic AI, and multi-model systems. - Experience with MLOps or LLMOps, including CI/CD automation, monitoring, governance, and model lifecycle management. - Proficiency in Python, machine learning frameworks, APIs, and REST services, plus enterprise integration and data engineering knowledge.

Benefits and work setup - Current Government of Canada Reliability clearance or higher is required when applying.