Senior AI Engineer
The role involves designing and implementing end-to-end Generative AI solutions, including RAG architectures and AI agents. The engineer will deploy scalable cloud-native architectures and implement MLOps/LLMOps practices within the Azure ecosystem.
- On-site
- Toronto, ON
- Posted Aug 4, 2026
- Apply by Sep 3, 2026
- 1 position
Job summary
TekStaff's Client has a current vacancy for a Senior AI Engineer Job Description Required Experience 7+ years of experience in AI/GEN AI/ML engineering, with strong expertise in Azure cloud environments Proven track record delivering end-to-end AI solutions in production Experience with Snowflake or modern enterprise data platforms Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field Core AI & Engineering Capabilities Generative AI & LLMs Hands-on experience building Generative AI applications (GPT, Claude, Gemini, etc.) Experience fine-tuning and optimizing LLMs for enterprise use cases Designing and implementing RAG (Retrieval-Augmented Generation) architectures: Retrieval & embeddings Vector search Grounding & context orchestration AI Agents & Orchestration Designing and building AI agents using frameworks such as: LangChain Semantic Kernel Azure OpenAI Service Azure Open AI Experience with: Multi-agent systems Tool/function calling Workflow automation and orchestration Azure AI & Platform Engineering Strong experience across the Azure AI ecosystem: Azure OpenAI Azure AI Search Azure AI Foundry Azure Machine Learning Azure Fabric Snowflake Integration with enterprise services: Azure Cognitive Services Azure Data Lake Azure Event Hub Experience deploying scalable solutions on: Azure Kubernetes Service (AKS) Distributed, cloud-native architectures Software Engineering Strong programming skills in Python Experience building APIs (FastAPI or similar) Experience with microservices architecture and enterprise system integration Familiarity with containerization (Docker/Kubernetes) MLOps, LLMOps & Governance Experience implementing MLOps / LLMOps practices: Azure DevOps, MLflow, CI/CD pipelines Model evaluation frameworks Monitoring, observability, performance tracking Strong understanding of Responsible AI practices: Security & data protection Risk management & guardrails Compliance with enterprise governance standards TekStaff may use artificial intelligence (AI) tools as part of the applicant screening process. However, applications will also be reviewed by a member of our Recruitment team to ensure a fair and thorough assessment.
What you’ll do
The role involves designing and implementing end-to-end Generative AI solutions, including RAG architectures and AI agents. The engineer will deploy scalable cloud-native architectures and implement MLOps/LLMOps practices within the Azure ecosystem.
Requirements
Candidates need 7+ years of experience in AI/ML engineering with strong expertise in Azure and Snowflake. A Bachelor's or Master's degree in Computer Science or a related field is required.
Listed skills
- PythonPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Generative AI
- LLMs
- RAG
- Azure OpenAI
- LangChain
- Semantic Kernel
- Python
- FastAPI
- Azure Kubernetes Service
- Snowflake
- MLOps
- LLMOps
- Vector Search
- Microservices
- Azure AI Search
- Azure Machine Learning
Job areas
- Software
- Technology
- Data & Analytics
- Engineering
- Finance & Accounting
Additional details
- Minimum education
- Bachelor’s degree
- Minimum experience
- 5+ years
- Apply by
- Sep 3, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available