Lead Agentic AI Solutions Architect
Location: Mississauga, Ontario, Canada (CAN, ON)
Work Arrangement: Hybrid – 2 days in the office per week
About the Role
- The client is seeking an experienced Lead Agentic AI Solutions Architect to lead the end-to-end delivery of enterprise AI and automation solutions that transform business operations and improve healthcare outcomes.
- This role owns the full lifecycle of Agentic AI and automation solution delivery, from strategy and architecture through implementation, deployment, and optimization.
- You will partner closely with business, product, engineering, and enterprise architecture teams to identify high-value opportunities, design scalable AI solutions, and ensure responsible AI practices are embedded throughout the development lifecycle.
- This role is ideal for a technology leader passionate about building enterprise-grade agentic systems powered by large language models, modern AI frameworks, and cloud-native platforms.
What You'll Do
- Own the full lifecycle of Agentic AI and automation solutions, from discovery and architecture through deployment and operational support.
- Identify, prioritize, and deliver high-impact AI use cases aligned with business strategies and measurable outcomes.
- Design scalable Agentic AI architectures integrated with Agent Hub, enterprise platforms, APIs, and business workflows.
- Lead technical design decisions involving LLMs, AI agents, retrieval systems, orchestration frameworks, and automation technologies.
- Partner with business and technology stakeholders to define requirements, solution roadmaps, and implementation strategies.
- Establish engineering standards, architecture patterns, governance controls, and reusable AI capabilities.
- Drive Responsible AI practices, including governance, security, observability, risk management, and human oversight.
- Mentor engineers and architects while promoting technical excellence, innovation, and continuous improvement.
Minimum Requirements
Degree or equivalent; typically requires 10+ years of relevant experience. Fewer years may be required with relevant Master's or Doctorate qualifications.
Critical Skills
- 10+ years of software engineering, solution architecture, application development, or platform engineering experience.
- 5+ years of experience designing and implementing AI-enabled enterprise solutions.
- Hands-on experience building AI, machine learning, automation, or intelligent workflow solutions in enterprise environments.
- Strong proficiency in Python and Agentic software engineering practices.
- Experience designing enterprise integrations using MCPs, APIs, microservices, and event-driven architectures.
- Proven experience leading technical delivery across multiple teams and stakeholders.
- Excellent communication, collaboration, and solution leadership skills.
Preferred Skills
- Strong understanding of Large Language Models (LLMs), tokenization, context windows, and model capabilities.
- Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, Claude Agent SDK, or similar frameworks.
- Experience designing function-calling patterns, tool integrations, and structured schemas.
- Expertise with Azure Cloud services, Azure AI Foundry, and cloud-native architecture patterns.
- Experience with Docker, Kubernetes, CI/CD pipelines, and modern deployment practices.
- Experience implementing Human-in-the-Loop processes for critical business workflows.
- Understanding of Responsible AI principles, governance frameworks, risk management, and compliance requirements.
Travel / Work Environment / Physical Requirements
- Position may require limited travel (up to 10%) for business meetings, workshops, or strategic planning sessions.
- Hybrid or remote work arrangements may be available based on business needs and location requirements.
- Ability to work at a computer workstation for extended periods and participate in virtual collaboration sessions.
