GenAI Engineer

Role: GenAI Engineer

Location: Toronto ON
Contract

We are looking for strong hands-on GenAI profiles with proven enterprise experience. This role requires deep expertise in Azure OpenAI RAG-based architectures and cloud-native application development. Candidates should be capable of leading solution design building PoCs and working directly with business and platform stakeholders. Profiles that do not meet the mandatory criteria will not be considered.

Role Summary

The Generative AI Engineer will participate in the design development and adoption of enterprise-scale AI solutions. This role blends hands-on engineering solution architecture to deliver secure scalable and business-aligned Generative AI platforms using Azure OpenAI and cloud-native technologies. The ideal candidate has strong experience delivering end-to-end AI-powered applications from data ingestion and model integration to APIs and lightweight user interfaces for internal tools PoCs and business-facing solutions. Deep frontend specialization is not required but the ability to independently deliver complete AI solutions is essential.

Key Responsibilities

• Design and implementation of Generative AI solutions using Azure OpenAI (GPT-4o GPT-5 embeddings RAG architectures).
• Build and validate Proofs of Concept (PoCs) to assess feasibility scalability performance and business value.
• Design and deploy RAG-based AI systems including vector search prompt orchestration and knowledge grounding.
• Deliver end-to-end AI applications including backend services APIs and lightweight UI components for AI-driven workflows.
• Actively leverage AI agents and agentic frameworks for tasks such as code generation testing refactoring workflow automation and intelligent orchestration.
• Develop and integrate custom copilots using Copilot Studio Azure AI Foundry Entra ID Microsoft Graph API and enterprise applications.
• Architect and build cloud-native applications using Azure Functions App Services and microservices on Azure Contianer Registry/AKS.
• Design data ingestion pipelines from SharePoint Cosmos DB and external APIs for AI-driven solutions.
• Ensure AI solutions meet enterprise security compliance and governance standards.
• Partner with product owners architects security teams and business stakeholders to drive AI adoption.
• Provide technical leadership through design reviews mentoring and best practice guidance.
• Contribute to AI standards reference architectures and operational runbooks.
• Coordination between Onshore & Offshore teams

Must-Have Requirements

• 8 years of experience in software platform or cloud engineering.
• 3 years of hands-on experience with AI/ML or Generative AI solutions.
• Strong experience with Azure OpenAI and LLM-based application development.
• Proven experience implementing RAG architectures and vector search solutions.
• Experience delivering end-to-end AI applications including backend services APIs and basic user interfaces for AI-driven solutions.
• Experience using AI agents or agentic workflows to assist with software development automation or intelligent orchestration.
• Solid background in Azure cloud services (Functions App Services ACR).
• Familiarity with AI observability including model monitoring logging and usage analytics.
• Hands-on experience with Azure AI Search Azure Document Intelligence or similar services.
• Strong programming experience in Python and or NodeJS/TypeScript.
• Experience with prompt engineering evaluation strategies and LLM performance tuning.
• Experience designing scalable resilient and secure enterprise systems.
• Excellent communication skills with the ability to translate business needs into technical solutions.
• Experience coordinating between onshore and offshore

Preferred / Nice-to-Have

• Experience implementing authentication and authorization using Entra ID managed identities and RBAC.
• Infrastructure as Code experience using Terraform or Bicep.
• CI/CD experience using GitHub Actions.
• Understanding of data privacy PII handling and responsible AI practices.
• Experience working in regulated or large enterprise environments.
• Exposure to Azure Document Intelligence Power Platform or Copilot Studio