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're hiring talent that AI can't replace to help us shape the future of information management. Join us.

Senior AI Developer (GenAI Enablement and Agentic Systems) in Waterloo, ON (Hybrid) OpenText’s AI Engineering and Enablement team is building the foundational components and developer experiences that power intelligent applications across our product portfolio.

Your Impact As a Senior AI Developer within the AI Engineering and Enablement team, you will contribute to building the intelligent components and runtime services that power next-generation agentic applications at OpenText. You’ll work on high-value GenAI capabilities such as retrieval-augmented generation (RAG), tool-based agents, vector search, and semantic orchestration.

In this role, you’ll implement shared components and contribute to fast-moving development projects that help scale GenAI adoption across our platform. You’ll collaborate closely with principal engineers, architects, and product teams to deliver robust agent flows, integrate shared tools and protocols like A2A and MCP, and extend the reusability of our internal AI foundation.

This position is ideal for an experienced developer who is enthusiastic about AI platforms, wants to deepen their expertise in agentic patterns, and enjoys working in cross-functional engineering teams.

What The Role Offers As a Senior AI Developer (GenAI Enablement and Agentic Systems) , you will:

• Developing and testing modular components for GenAI-based systems, including RAG pipelines, agent workflows, and tool integration services.
• Implementing agent logic such as tool selection, memory management, and decision branching under guidance from senior engineers and architects.
• Supporting the development of multi-agent interaction patterns, including message handling, parallel execution, and structured delegation.
• Participating in the integration of Model Context Protocol (MCP) and Agent-to-Agent (A2A) coordination into running systems and orchestration layers.
• Contributing to the integration of vector databases, hybrid search pipelines, and embedding-based retrieval into production environments.
• Writing Python services using FastAPI, extending shared modules, and helping validate new capabilities in staging or sandbox environments.
• Collaborating with peers across engineering, QA, and product management to ensure solution completeness, performance, and maintainability.

What You Need To Succeed

• Writing high-quality Python code with clear structure and reusable patterns, especially in service-oriented architectures.
• Using FastAPI or similar frameworks to build performant and secure AI-related APIs.
• Applying orchestration libraries like LangChain, LangGraph, CrewAI, or related tooling to implement agentic patterns.
• Understanding agent flow constructs such as tool chaining, memory contexts, and semantic grounding.
• Following architectural guidance and contributing to internal standards for reusable GenAI components.
• Collaborating in cross-functional teams, incorporating feedback, and participating in code reviews and technical discussions.
• Navigating surrounding technologies such as Java and TypeScript, particularly when consuming or integrating platform APIs.

What It Takes

• 6–8 years of software development experience, including 1–2 years working with LLMs or GenAI-based systems.
• Strong programming experience with Python and practical experience using FastAPI to build backend services.
• Familiarity with frameworks like LangChain, LangGraph, or CrewAI, and eagerness to deepen your agent orchestration expertise.
• Exposure to RAG pipelines, vector databases, and embedding techniques in functional or experimental settings.
• Awareness of A2A interaction patterns and MCP-based agent-to-tool flows, with some hands-on implementation experience.
• Interest in applying or integrating knowledge graph–driven data into GenAI workflows is a plus.
• Ability to work independently on scoped components, ask the right questions, and grow toward broader architectural awareness.
• Strong technical collaboration, version control, and documentation skills.

One Last Thing OpenText is more than just a corporation, it's a global community where trust is foundational, the bar is raised, and outcomes are owned.

Join us on our mission to drive positive change through privacy, technology, and collaboration. At OpenText, we don't just have a culture; we have character. Choose us because you want to be part of a company that embraces innovation and empowers its employees to make a difference.

OpenText's efforts to build an inclusive work environment go beyond simply complying with applicable laws. Our Employment Equity and Diversity Policy provides direction on maintaining a working environment that is inclusive of everyone, regardless of culture, national origin, race, color, gender, gender identification, sexual orientation, family status, age, veteran status, disability, religion, or other basis protected by applicable laws.

If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please contact us at hr@opentext.com. Our proactive approach fosters collaboration, innovation, and personal growth, enriching OpenText's vibrant workplace.