Generative AI Engineer

Toronto, ON
Hybrid
Posted Sep 9, 2026
1 position

Opens an external site

Employment type: Contract
Experience level: Senior · 6+ years
Apply by: Oct 9, 2026
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week
Seniority: Associate
Application method: Direct apply is available

Job summary

Design, develop, and deploy production-grade Generative AI solutions and intelligent agents using RAG architectures. Build scalable APIs and microservices while implementing MLOps practices on Azure cloud platforms.

Job details

Senior Generative AI Engineer / AI Engineer PrecisionERP/IT is seeking a Senior Generative AI Engineer to design, build, and scale enterprise AI systems, Generative AI applications, and intelligent agents. This is a 1-year contract position based in downtown Toronto. The role requires onsite presence at least 3 days per week. Responsibilities Design, develop, and deploy production-grade AI and Generative AI solutions. Build enterprise GenAI applications using LLMs, RAG, embeddings, vector search, and AI agents. Design and implement Retrieval-Augmented Generation architectures for enterprise use cases. Develop AI agents using frameworks such as LangChain, Semantic Kernel, and Azure OpenAI. Fine-tune, optimize, and evaluate LLMs for business and enterprise applications. Build scalable APIs, microservices, and enterprise system integrations. Deploy AI/ML solutions on Azure cloud and Azure Kubernetes Service. Implement MLOps practices for model deployment, monitoring, and continuous improvement. Work with Snowflake and enterprise data platforms to support AI workloads. Required Qualifications 6+ years of experience in AI, Generative AI, or Machine Learning engineering. Strong experience working in Azure cloud environments. Hands-on experience building end-to-end AI solutions in production. Experience building Generative AI applications using LLMs, RAG, and AI agents. Experience with Azure OpenAI, LangChain, Semantic Kernel, or similar AI frameworks. Experience with Snowflake or other enterprise data platforms. Strong Python programming skills. Experience building APIs and working with microservices architecture. Experience with Azure Kubernetes Service or similar container platforms. Experience with MLOps, model deployment, monitoring, and optimization. Nice to Have Experience with Azure AI Search, Azure AI Foundry, Azure Machine Learning, or Microsoft Fabric. Experience with LLMOps, Responsible AI, guardrails, observability, and enterprise AI governance. Experience working in large enterprise or regulated environments.

What you’ll do

Requirements

Requires over 6 years of experience in AI/ML engineering with strong proficiency in Python and Azure cloud environments. Must have hands-on experience building end-to-end GenAI applications using frameworks like LangChain or Semantic Kernel.