Lead Applied AI Scientist – Agentic AI & Enterprise Workflow Automation

Location: Mississauga, Greater Toronto Area, Canada
Job Type: Contract
Experience: 7+ Years

ex-Microsoft or Ex-Amazon candidates preferred

Job Overview

We are seeking an experienced Lead Applied AI Scientist to design, develop, and deploy advanced Generative AI and Agentic AI solutions for enterprise environments.

The ideal candidate will have strong hands-on experience in Python, Large Language Models (LLMs), multi-agent architectures, reasoning agents, RAG, and enterprise AI integrations.

This role requires a combination of advanced AI engineering, solution architecture, technical leadership, and business-facing communication skills.

We are looking for professionals who have successfully transformed AI concepts and proof-of-concepts into scalable, production-ready enterprise applications.

Key Responsibilities

• Design, develop, and deploy advanced Agentic AI and multi-agent systems.

• Build autonomous, reasoning, planning, and workflow-based AI agents.

• Develop production-grade AI applications using Python.

• Integrate LLM platforms such as Azure OpenAI, OpenAI, Anthropic, or equivalent technologies.

• Design and implement RAG architectures, semantic search, vector databases, and agent memory.

• Develop agent orchestration and tool-calling capabilities for complex business workflows.

• Integrate AI solutions with enterprise platforms such as SAP, Oracle, Snowflake, Databricks, and REST APIs.

• Build intelligent workflow automation solutions to improve enterprise operational efficiency.

• Implement LLM evaluation, observability, governance, safety, and human-in-the-loop mechanisms.

• Lead AI solution development from proof-of-concept through production deployment.

• Collaborate directly with business leaders and stakeholders to translate operational challenges into AI-driven solutions.

• Provide technical leadership, architecture guidance, and mentoring to AI engineering teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical discipline.

• 7+ years of experience in AI/ML engineering, applied AI, or related technology domains.

• Minimum 2 years of hands-on experience building Generative AI, Agentic AI, or LLM-based applications.

• Strong programming and application development experience using Python.

• Hands-on experience with Azure OpenAI, OpenAI APIs, Anthropic, or similar LLM platforms.

• Experience designing and developing multi-agent systems, reasoning agents, planning agents, and tool-using agents.

• Strong understanding of Retrieval-Augmented Generation (RAG), vector databases, semantic search, and agent memory.

• Experience integrating AI applications with enterprise platforms, APIs, and business workflows.

• Demonstrated experience taking AI solutions from proof-of-concept to production deployment.

• Strong communication, problem-solving, and stakeholder-management skills.

Preferred Qualifications

• Experience with LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.

• Experience in Supply Chain, Manufacturing, Procurement, Logistics, Planning, or Operations.

• Knowledge of LLM evaluation frameworks, AI observability, governance, safety, and guardrails.

• Experience implementing human-in-the-loop controls and responsible AI practices.

• Experience working with enterprise cloud platforms, including Microsoft Azure or AWS.

• Previous experience leading small AI engineering teams or technical workstreams.

• Experience working with senior business stakeholders and enterprise leadership teams.

Core Technical Skills

• Python Development

• Agentic AI & Multi-Agent Systems

• Generative AI & Large Language Models (LLMs)

• Azure OpenAI / OpenAI / Anthropic

• LangGraph / LangChain / AutoGen / CrewAI

• Retrieval-Augmented Generation (RAG)

• Vector Databases & Semantic Search

• AI Reasoning & Planning Agents

• Enterprise AI Integration

• SAP / Oracle / Snowflake / Databricks

• LLM Evaluation & AI Observability

• Enterprise Workflow Automation

Ideal Candidate Profile

The ideal candidate is a senior AI professional with strong hands-on expertise in designing and deploying production-grade Agentic AI solutions.

Candidates should be capable of architecting intelligent multi-agent systems, developing advanced reasoning capabilities, integrating AI into enterprise applications, and leading AI initiatives from concept to production.

Professionals with experience building enterprise AI products and solving complex business problems using autonomous agents and LLM-based technologies are highly desirable.