Lead Agentic AI Solutions Architect

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 Lang Chain, Lang Graph, Semantic Kernel, Auto Gen, 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.