Principal AI Architect

OPENTEXT - THE INFORMATION COMPANY

OpenText is a global leader in information management, where innovation, creativity, and collaboration are the key components of our corporate culture. As a member of our team, you will have the opportunity to partner with the most highly regarded companies in the world, tackle complex issues, and contribute to projects that shape the future of digital transformation.

AI-First. Future-Driven. Human-Centered.

At OpenText, AI is at the heart of everything we do—powering innovation, transforming work, and empowering digital knowledge workers. We are hiring talent AI can't replace to help us shape the future of information management. Join us.

Job Title: Principal AI Architect

Job Location: Richmond Hill/ Waterloo, ON (Office based)

OpenText's AI Development and Enablement organization designs and delivers AI solutions that power customer-facing products, agents, and intelligent workflows. We work across the product portfolio, bringing new ideas into applications and building the shared AI technology that helps teams innovate faster.

As a Principal AI Architect, you will turn advances in AI into applications and agents that solve enterprise problems. You will own architecture for defined solutions and platform components, working with product and engineering teams from early experimentation through production.

You will also design the AI lifecycle and platform primitives that help teams build, deploy, and operate these solutions at scale. This hands-on role offers room to explore new approaches, build proofs of concept, and shape capabilities used across OpenText products. You will stay close to implementation, helping teams work through design choices and learning from how their solutions perform in production.

You Are Great At

• Architecting AI solutions and agent workflows that connect enterprise information, applications, and tools.

• Designing how agents retrieve and assemble grounded context, use tools and memory, and coordinate work. Choosing among deterministic workflows, individual agents, and multi-agent patterns to meet the problem's needs with appropriate reliability and human oversight.

• Developing prototypes and reference implementations to validate architecture and guide teams into production.

• Designing lifecycle capabilities for evaluation, versioning, deployment, observability, and ongoing improvement, so changes to models, prompts, and agent behavior can be assessed and introduced confidently.

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