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Senior Analyst, Enterprise AI & Gen AI

University Health Network

Toronto, ON

Job typeFull-time
SpecialtyTechnical
Compensation$81,549 – $122,342/year
Posted3 weeks ago

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Location200 Elizabeth Street M5G 2C4, Toronto, ON, CAOpen

eHealth role summary

Position designs, develops, and operationalizes AI/Generative AI solutions for clinical, research, operational and corporate functions at a major hospital, integrating with enterprise health data platforms and addressing privacy/responsible AI in a regulated healthcare setting.

About this role

Union: Non-union
Number of vacancies: 1
New or Replacement Position: New
Site: Toronto General Hospital
Department: Data & Analytics
Reports to: Principle Advanced Analytics Consultant
Salary Range: $81,549 - $122,342 per annum
Hours: 37.5 hours per week
Status: Permanent Full-Time
Closing Date: September 2, 2026

Position Summary
The Senior Analyst, AI leads the design, development, implementation, and operationalization of enterprise Artificial Intelligence (AI) and Generative AI solutions that support clinical, research, operational, and corporate objectives. The role develops scalable AI architectures, agentic AI workflows, and reusable enterprise AI capabilities using cloud-based platforms and modern AI technologies. Working closely with business and technical stakeholders, the incumbent provides expert consultation, leads complex AI initiatives, and integrates AI solutions with enterprise systems and data platforms. The Senior Analyst, AI establishes governance frameworks, standards, and best practices to ensure AI solutions are secure, compliant, reliable, and aligned with organizational priorities.

Duties

  • Design, develop, and operationalize Enterprise AI and Agentic AI solutions using Azure AI Foundry and the Microsoft Azure ecosystem
  • Build reusable enterprise AI capabilities including LLM applications, AI agents, RAG, embeddings, vector search, and intelligent assistants
  • Establish enterprise AI architectures, development standards, governance frameworks, and best practices for scalable AI adoption
  • Develop and integrate AI services, APIs, and workflows with enterprise data platforms, applications, and business processes
  • Build agentic workflows and multi-agent solutions that automate and enhance clinical, operational, research, and corporate functions
  • Implement MLOps/LLMOps practices, deployment pipelines, monitoring, evaluation, and lifecycle management for AI solutions
  • Ensure AI solutions comply with privacy, security, responsible AI, and healthcare regulatory requirements
  • Collaborate with business, clinical, research, and technical stakeholders to identify and deliver AI-enabled transformation initiatives

Qualifications

  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
  • 3-5 years of experience delivering AI, machine learning, Generative AI, or enterprise analytics solutions in production environments
  • Strong programming skills in Python and SQL
  • Experience building and deploying AI/ML and Generative AI solutions using enterprise platforms such as Azure AI Foundry, Azure Machine Learning, or Azure OpenAI
  • Experience with LLM applications, prompt engineering, RAG, embeddings, vector search, and enterprise knowledge retrieval
  • Experience developing AI agents, agentic workflows, tool-calling systems, or intelligent assistants
  • Experience implementing scalable AI services, APIs, integration patterns, and AI lifecycle management practices
  • Knowledge of AI governance, responsible AI, privacy, security, and regulated environments
  • Experience with Azure AI Foundry Agent Service, Semantic Kernel, Microsoft Agent Framework, LangChain, LangGraph, or similar technologies is an asset 
  • Experience designing enterprise AI platforms, reusable AI services, reference architectures, and AI enablement frameworks is an asset 
  • Experience with AI evaluation, observability, MLOps/LLMOps, CI/CD, and cloud-native deployment practices is an asset 
  • Experience with Azure AI Search, Microsoft Fabric, Databricks, Azure Data Lake, or enterprise data platforms is an asset 
  • Experience in healthcare, research, or other regulated industries is an asset 

Additional Information

Why join UHN?

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor, allowing you to find value where it matters most to you, now and throughout your career at UHN.

  • Competitive offer packages
  • Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/)
  • Close access to Transit and UHN shuttle service
  • A flexible work environment
  • Opportunities for development and promotions within a large organization
  • Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)

Current UHN employees must have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, to be eligible for consideration.

All applications must be submitted before the posting close date.

UHN uses email to communicate with selected candidates.  Please ensure you check your email regularly. At University Health Network (UHN), artificial intelligence technologies may be used to assist in the screening, assessment, and selection of candidates for this position.

Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading, inaccurate or incorrect, UHN reserves the right to discontinue with the consideration of their application.

UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.