Staff Product Manager AI Platform positions focus on delivering results in their domain. This page aggregates open Staff Product Manager AI Platform roles and what employers typically expect.
**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Product Manager- AI Platform based in Canada.** This role offers the opportunity to define the future of enterprise AI platforms by shaping the systems that power next-generation intelligent experiences. You will own the vision, strategy, and roadmap for a foundational AI platform supporting agentic workflows, automation, and AI-driven products at scale. Working across engineering, data, security, and product teams, you will translate complex technical challenges into scalable product solutions. The position requires a strong systems mindset, deep technical judgment, and the ability to balance innovation with enterprise reliability. You will influence how AI capabilities are built, governed, evaluated, and adopted across a growing technology ecosystem. This is a high-impact opportunity for a product leader passionate about AI infrastructure, developer experience, and building trusted intelligent systems. ### Accountabilities: As a Staff Product Manager, AI Platform, you will lead the development and evolution of a shared AI platform that enables teams to build reliable, scalable, and secure AI-powered experiences. You will operate as a senior individual contributor, driving product strategy while collaborating with technical and business stakeholders to deliver enterprise-grade AI capabilities. - Own the product vision, strategy, and roadmap for an AI platform focused on reliability, safety, scalability, and measurable business outcomes. - Define how AI agents operate in production, including orchestration patterns, context management, tool usage, workflows, and execution models. - Establish scalable platform standards, including APIs, configuration frameworks, versioning strategies, and lifecycle management practices. - Partner with engineering, data, security, and product teams to make decisions around architecture, infrastructure, performance, and operational complexity. - Create adoption strategies through developer tools, shared components, documentation, and standardized workflows that enable teams to build efficiently. - Establish quality, governance, and safety frameworks including evaluation processes, monitoring, access controls, and auditability. - Shape the developer and product experience for building, testing, debugging, and managing AI-powered solutions. - Evaluate build-versus-buy decisions and guide external technology integrations through well-defined platform approaches. - Define success metrics and measure platform impact through adoption, performance, quality, reuse, and cost efficiency. - Stay informed on advancements in AI agents, orchestration frameworks, and evaluation methodologies to guide practical product decisions. ## Requirements: The ideal candidate brings extensive product leadership experience combined with strong technical understanding of AI systems, platforms, and enterprise software environments. You should be comfortable influencing cross-functional teams, defining complex platform strategies, and making decisions that balance innovation, reliability, and scalability. - 8+ years of product management experience, including significant experience building platforms, infrastructure products, or developer-facing solutions. - Strong technical foundation through engineering, computer science, or equivalent hands-on experience with complex software systems. - Deep understanding of AI-powered systems, distributed architectures, LLM-based agents, retrieval workflows, multi-step automation, and tool-based interactions. - Experience defining and scaling platform contracts, APIs, configuration models, and lifecycle management strategies. - Proven ability to introduce governance, standards, and quality frameworks while maintaining product velocity. - Strong knowledge of AI system evaluation, observability, monitoring, and regression testing practices. - Experience…