Onsite 3 days/week

About the role

- A leading financial services institution is growing its AI practice and is looking for an AI Engineer to design, build and run production AI solutions on Azure and Databricks. You will take generative AI and machine learning use cases from prototype to production, with the reliability, monitoring and governance a regulated enterprise requires.

Key responsibilities

- Design, build and deploy generative AI solutions on Azure AI Foundry, including RAG patterns, agents, prompt flows and model evaluation.
- Establish and run LLMOps practices: prompt and model versioning, evaluation pipelines, guardrails, content safety, cost and latency monitoring.
- Build and maintain MLOps pipelines for training, deployment, monitoring and retraining of machine learning models.
- Develop and configure Databricks Genie spaces so business users can query governed data in natural language, including curating instructions, sample queries and trusted assets.
- Work with data engineering teams on Databricks (Delta Lake, Unity Catalog, MLflow) to prepare and govern the data AI solutions depend on.
- Partner with business stakeholders, product owners and risk teams to turn use cases into secure, compliant solutions.
- Apply responsible AI practices, including model risk management, explainability, data privacy and audit requirements.
- Contribute to the practice's reusable patterns, standards and engineering best practices.



Required qualifications
- 5+ years in software, data or machine learning engineering, including at least 2 years delivering generative AI or LLM solutions in production.
- Hands-on experience with Azure AI Foundry and Azure OpenAI Service.
- Proven LLMOps and MLOps experience, including CI/CD for models, evaluation, monitoring and drift detection.
- Practical experience with Databricks, including MLflow and Unity Catalog; experience configuring Databricks Genie (AI/BI Genie).
- Robust Python skills and solid SQL.
- Experience with Azure services such as Azure AI Search, Azure Machine Learning, Azure Functions and Key Vault.
- Experience with CI/CD tooling such as Azure DevOps or GitHub Actions.
- Strong communication skills and comfort working with business and technical audiences. Nice to have
- Experience in banking, insurance or other regulated financial services.
- Familiarity with agent frameworks such as Semantic Kernel, LangChain or LangGraph.
- Microsoft certifications such as Azure AI Engineer Associate (AI-102); Databricks Machine Learning or Generative AI Engineer certification. This posting is for an existing vacancy. Artificial intelligence tools may be used to screen, assess or select applicants as part of our recruitment process. Accommodations are available on request for candidates taking part in all aspects of the selection process.

📌 Artificial Intelligence Engineer (Greater Toronto Area)
🏢 Fortiv Technical
📍 Greater Toronto Area