Principal Product Manager

Description:

Principal Product Manager, Model Services and AI Engineering (Hybrid) The AI Engineering and Enablement organization leads OpenText’s AI innovation strategy, shaping how generative and agentic AI are transformed into real products and customer-facing solutions. We work across product, engineering, and research to deliver AI capabilities that power intelligent content, secure workflows, and enterprise-scale automation across OpenText’s portfolio.

Our focus goes beyond platforms and tooling to building AI products, experiences, and shared foundations that accelerate innovation while maintaining the trust, security, and governance required in enterprise and regulated environments. From agentic development and orchestration to AI-powered solutions built on trusted content, we enable OpenText teams and customers to realize the full potential of AI at scale.

Your Impact You will own the strategy and roadmap for OpenText’s Model Services platform. This includes model selection, tuning, optimization, evaluation, routing, cost and performance management, and lifecycle operations. This is a technical platform product role focused on delivering reliable, governed, and reusable large language model capabilities for all engineering teams.

You will work closely with engineering and architecture to evolve the model gateway, tuning pipelines, safety mechanisms, and ModelOps frameworks. You will also support integration with secondary components such as retrieval augmented generation, agentic frameworks, and internal developer tooling.

What The Role Offers

• Define strategy and roadmaps for Model Services, including the model gateway, routing, tuning, evaluation, and lifecycle management.
• Translate technical and architectural patterns into reusable platform capabilities.
• Lead planning and launch of model infrastructure components with engineering partners.
• Balance cost, performance, safety, and developer experience in product decisions.
• Conduct market and competitive research on commercial and open source models, runtimes, and tuning methods.
• Support downstream integrations into retrieval augmented generation, agentic systems, and internal tooling where needed.

What You Need To Succeed

• Ten or more years in product management or platform leadership, including three or more years in AI, ML, or ModelOps.
• Strong understanding of large language model operations, including selection, inference optimization, routing, tuning, evaluation, and safety.
• Experience with model lifecycle management, telemetry, benchmarking, and capacity and cost planning.
• Familiarity, preferred but secondary, with generative AI frameworks or enterprise governance patterns such as LangChain, LangGraph, MCP, or A2A.
• Demonstrated success shipping enterprise platform or developer facing products.
• Ability to translate complex technical requirements into clear product decisions and actionable roadmaps.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.