AI Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, develop, deploy, and maintain enterprise-level AI, machine learning, and advanced analytics solutions.

• Create and integrate AI-driven applications utilizing Azure AI Services, Azure OpenAI Service, Azure Machine Learning, and other Microsoft AI technologies.

• Develop and operationalize Generative AI solutions leveraging LLMs, prompt engineering, RAG, semantic search, and vector search.

• Design and implement scalable AI platforms and cloud-native solutions using Microsoft Fabric and Microsoft Azure.

• Create AI and machine learning applications utilizing Python, machine learning frameworks, APIs, and RESTful services.

• Implement and manage MLOps and LLMOps practices, including deployment pipelines, model lifecycle management, monitoring, testing, and continuous enhancement.

• Utilize Azure DevOps, GitHub, MLflow, and CI/CD pipelines to develop, deploy, and operationalize AI solutions.

• Collaborate with both business and technical stakeholders to incorporate AI and machine learning into enterprise applications and business processes.

• Design secure, scalable, and reliable AI solutions that align with organizational architecture and technology standards.

• Apply Responsible AI principles and support governance, compliance, security, and risk management requirements.

⛳️ Requirements

• A minimum of 5 years of experience in delivering Artificial Intelligence, Machine Learning, Advanced Analytics, Data Science, or related technology solutions.

• Strong expertise in Azure AI services, machine learning engineering, cloud-native architectures, and Responsible AI practices.

• Extensive experience in machine learning, agentic AI, model training, prompting techniques, and modern AI models and multi-model AI systems.

• Proven expertise in AI solution architecture and scalable, secure, cloud-native AI solutions.

• Hands-on experience in developing and deploying Generative AI and LLM-based applications, including prompt engineering, RAG architectures, semantic search, and vector search.

• Experience in implementing and managing MLOps and LLMOps practices, including CI/CD automation, model monitoring, model governance, and lifecycle management.

• Strong experience with Azure AI Services, Azure OpenAI Service, Azure Machine Learning, Microsoft Fabric, and Azure cloud technologies.

• Proficiency in Python, machine learning frameworks, API development, REST services, and AI application development.

• Experience in designing and implementing enterprise integrations, APIs, and AI-enabled business applications.

• Strong understanding of data engineering, analytics platforms, and AI-ready data architectures.

• Knowledge of security, governance, compliance requirements, and Responsible AI principles within enterprise environments.

• Excellent analytical, problem-solving, communication, and stakeholder management skills.

• Reliability Status security clearance or higher is required at the time of application.

🏝️ Benefits

• Collaborative environment.

• Mentorship and coaching.

• Knowledge-sharing and continuous improvement opportunities.

• Inclusive hiring practices.

• Recruitment-process accommodation support.