Senior Analyst, AI
About The Position
This is a new, permanent, full-time position within the Data & Analytics department at Toronto General Hospital. The role involves designing, building, and maintaining enterprise vector databases for AI and LLM-powered applications. The successful candidate will develop embedding pipelines, implement vector indexing and semantic search, and optimize retrieval performance. Integration with platforms like Azure AI Search, Qdrant, and Pinecone is expected, along with building scalable data ingestion and embedding refresh pipelines. The role also supports agentic AI workflows and establishes standards for vector storage, retrieval evaluation, governance, and operational monitoring.
Requirements
- Bachelor degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
- 3–5 years of hands-on experience delivering AI, machine learning, or data science solutions in production
- Strong programming skills in Python and SQL
- Experience with machine learning frameworks such as scikit-learn or XGBoost
- Experience with Generative AI technologies including LLMs, prompt engineering, RAG pipelines, and embeddings
- Experience building vector databases, semantic search systems, and retrieval architectures
- Experience with vector databases such as Azure AI Search, Qdrant, or Pinecone
- Experience with Azure Machine Learning and Azure AI Foundry
- Proficiency in scalable AI workflows, APIs, deployment pipelines, and operationalization
- Familiarity with responsible AI, governance, privacy, and regulated environments
Nice To Haves
- Experience with LangChain, Semantic Kernel, or agentic AI frameworks
- Familiarity with MLOps / LLMOps and CI/CD practices
- Experience in healthcare, research, or other regulated industries
- Exposure to enterprise AI platform design and AI enablement initiatives
Responsibilities
- Design, build, and maintain enterprise vector databases for AI and LLM-powered applications
- Develop embedding pipelines for structured and unstructured healthcare data
- Implement vector indexing, semantic search, and Retrieval-Augmented Generation (RAG) architectures
- Optimize retrieval performance, chunking strategies, metadata filtering, and similarity search accuracy
- Integrate vector databases with Azure AI Search, Qdrant, Pinecone, or similar platforms
- Build scalable data ingestion and embedding refresh pipelines for continuous AI operations
- Support agentic AI workflows with memory, context retrieval, and tool orchestration capabilities
- Establish standards and best practices for vector storage, retrieval evaluation, governance, and operational monitoring
Benefits
- Competitive offer packages
- Member of the Healthcare of Ontario Pension Plan (HOOPP)
- 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.)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
