Lead Applied AI Scientist - Deep/Reasoning Agents (Healthcare life science/Medical Device)
- Mississauga, ON, Canada
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Original job description
Role: Lead Applied AI Scientist - Deep/Reasoning Agents (Healthcare life science/Medical Device)
Location: Mississauga, Greater Toronto
Type: Long term contract
Exp: 7+ Years
Must Have
- 7+ years in AI/ML, with at least 2 years building GenAI, agentic AI, or LLM-based solutions.
- Strong Python development skills and ability to build production-grade applications.
- Hands-on experience with Azure OpenAI, OpenAI, Anthropic, or similar LLM platforms.
- Experience designing and orchestrating multi-agent systems, planning agents, workflow agents, and tool-using agents.
- Deep understanding of RAG, vector databases, semantic search, memory, and evaluation frameworks.
- Experience integrating AI into enterprise systems such as SAP, Oracle, Snowflake, Databricks, APIs, and business workflows.
- Ability to work directly with business leaders to translate operational problems into AI solutions.
- Experience building AI products from proof-of-concept through production deployment.
- Strong communication skills with executive-facing and business-facing stakeholders.
Preferred
- Supply Chain, Manufacturing, Procurement, Logistics, Planning, or Operations experience.
- Experience with LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.
- Experience with AI observability, evaluation, governance, safety, and human-in-the-loop controls.
- Background leading small AI teams or technical workstreams
More about this job
Responsibilities
Lead the design and development of production-grade AI solutions, including multi-agent systems, planning and workflow agents, and tool-using agents. Work with business leaders to translate operational challenges into AI products and integrate them with enterprise systems and workflows.
Requirements
Requires at least seven years of AI/ML experience, including two or more years building generative AI, agentic AI, or LLM-based solutions, along with strong Python and hands-on experience with LLM platforms. Candidates should have expertise in agent orchestration, RAG, vector databases, enterprise integration, and production deployment; supply chain or operations experience and experience leading AI teams are preferred.
Skills
- Python
- Generative AI
- Agentic AI
- Large Language Models
- Multi-Agent Systems
- Retrieval-Augmented Generation
- Vector Databases
- Semantic Search
- AI Evaluation
- Azure OpenAI
- Production AI Deployment
- Stakeholder Communication
- AI Governance
- Human-in-the-Loop Controls
- Technical Leadership
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Management & Leadership
- Healthcare
Keywords
- Artificial Intelligence
- Machine Learning
- Generative AI
- Agentic AI
- Large Language Models
- Python
- Azure OpenAI
- OpenAI
- Anthropic
- Multi-Agent Systems
- Planning Agents
- Workflow Agents
- Tool-Using Agents
- Retrieval-Augmented Generation
- Vector Databases
- Semantic Search
- Memory
- Evaluation Frameworks
- SAP
- Oracle
- Snowflake
- Databricks
- LangGraph
- Semantic Kernel
- AutoGen
- CrewAI
- AI Observability
- AI Governance
- AI Safety
- Human-in-the-Loop