Sr. Principal AI Software Architect

Job Title:

Sr. Principal Software Architect (AI)

Job Location:

Richmond Hill, ON Hybrid (Tues, Wed, Thurs in-office & Mon, Fri- WFH)

Open Text 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 Open Text, AI is at the heart of everything we do—powering innovation, transforming work, and empowering digital knowledge workers. We’re hiring talent that AI can’t replace to help us shape the future of information management. Join us.

The AI Engineering and Enablement organization defines and evolves Open Text’s AI architecture and technical foundations, enabling teams to build secure, scalable, and production‑grade AI solutions across the enterprise. We operate at the intersection of platform engineering, applied AI, and product innovation, translating emerging AI capabilities into real‑world enterprise solutions.

This organization partners closely with engineering, product, and architecture teams to establish modern AI patterns, reference architectures, and best practices that accelerate adoption while maintaining reliability, security, and governance.

The Opportunity
As Sr. Principal Software Architect (AI), you will be a hands‑on technical leader and architectural partner responsible for shaping how AI solutions are designed, built, evaluated, and evolved  will work closely with architects and development teams to design, review, and improve modern RAG and agentic solutions, both new and existing.

This role is intentionally very hands‑on. You are expected to prototype, build proof‑of‑concepts, create starter projects, and validate architectural approaches in code. You will help teams adopt best practices across the full AI lifecycle, including prompt design, evaluation, observability, and continuous improvement.

This role requires deep technical credibility, strong enterprise experience, and the ability to guide teams through practical, real‑world AI architecture challenges.

You Are Great At

Designing and reviewing modern RAG pipelines and agentic systems for enterprise use cases.

Building and evolving agent orchestration and agent‑to‑agent solutions, including task delegation and tool calling.

Creating hands‑on prototypes, POCs, and starter templates to guide development teams.

Advising teams on prompt engineering best practices, evaluation strategies, and observability patterns.

Identifying architectural gaps and helping teams refactor or improve existing AI solutions.

Working closely with architects and developers to translate AI patterns into production‑ready designs.

Staying current with AI frameworks, tools, and research, and applying them pragmatically.

Explaining complex AI architecture decisions clearly and effectively.

Technology Stack & Focus Areas

Strong experience in the following areas is highly preferred:

Primary

Languages:

Python (primary), JavaScript / Type Script, Java

AI & Agentic Frameworks:
Lang Graph (highly preferred), Google ADK (highly preferred)

LLM‑based agent frameworks and orchestration patterns

AI Techniques & Practices:
Retrieval‑Augmented Generation (RAG), Prompt engineering and prompt management, Evaluation frameworks and quality measurement, Observability, tracing, and debugging of AI systems

Cloud & Platforms:
Google Vertex AI (strong preference),

Experience with AWS or Azure AI services, Containerized and cloud‑native AI deployments

Application & Platform Architecture:
FastAPI and modern backend frameworks, Microservices and API‑driven architectures, Event‑driven and scalable runtime systems

What It Takes

12+ years of software engineering experience, with significant time in principal or architect‑level roles.

Proven, hands‑on experience building and evolving enterprise AI solutions.

Deep understanding of the end‑to‑end AI lifecycle, from experimentation to production and optimization.

Strong ability to evaluate, adjust, and improve AI systems…