Lead Applied AI Scientist
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
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Job details
- Job type
- Contract
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- Posting language
- English
- Posted
Original job description
JD is as below:
Target ex-Microsoft or Ex-Amazon candidates , there are lot of AI resources came out from these companies.
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
Design and build production-grade AI applications, including LLM-based and multi-agent solutions, and integrate them with enterprise systems and business workflows. Work with business leaders to translate operational challenges into AI products, taking solutions from proof of concept through production deployment and leading small teams or technical workstreams.
Requirements
Requires 7+ years of AI/ML experience, including at least 2 years building generative AI, agentic AI, or LLM-based solutions, along with strong Python skills and hands-on experience with LLM platforms. Candidates should have expertise in multi-agent systems, RAG, vector databases, enterprise integrations, and stakeholder communication; supply chain or operations experience and familiarity with agent frameworks and AI governance are preferred.
Skills
- Python
- Generative AI
- Agentic AI
- Large Language Models
- Multi-Agent Systems
- Retrieval-Augmented Generation
- Vector Databases
- Semantic Search
- Azure OpenAI
- AI Evaluation
- Production Deployment
- AI Governance
- Human-in-the-Loop Controls
- Technical Leadership
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Science & Research
- Management & Leadership
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
- Human-in-the-Loop
- Supply Chain