openleverjobgether
Staff Product Manager (Agentic)
Jobgether
LocationCanada
EmploymentFull-time
Posted2026-08-21T04:42:11.014000+00:00
Last observed2026-08-26 21:51:40.410433
Job idjobgether-jobgether:lever:2bfc13ed-e10b-4d5d-8777-0393ab1d8348
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 (Agentic) based in Canada. This is a high-impact product leadership opportunity focused on shaping the next generation of AI-powered B2B SaaS experiences. You will own the vision, strategy, and execution of an agentic product initiative designed to automate complex proposal workflows. The role combines product discovery, AI innovation, customer research, and commercial strategy from early validation through scaled adoption. You’ll work closely with engineering, design, AI/ML, customers, and senior stakeholders in a highly autonomous environment. A key challenge will be balancing intelligent automation with customer trust, human oversight, reliability, and adoption. You’ll have the opportunity to establish a new product paradigm while working alongside an established, high-usage platform. This role is ideal for an entrepreneurial product leader who thrives on ambiguity, measurable outcomes, rapid experimentation, and building products that genuinely change how customers work. Define and own the product vision, strategy, roadmap, and success metrics for the assigned agentic product area, translating business objectives and market opportunities into a clear path from early validation to scaled adoption. Lead product discovery by validating customer problems, proposed solutions, willingness to pay, and success criteria before significant investment, using real-world feedback and measurable evidence to guide decisions. Partner closely with engineering, design, and AI/ML teams to build and launch agentic B2B SaaS experiences, maintaining strong alignment while making informed decisions around model selection, orchestration, reliability, latency, context, and other technical trade-offs. Establish a compelling approach to agentic experiences, including when AI should operate autonomously and when human intervention, approval, or control is required to build trust and deliver reliable outcomes. Drive the product lifecycle from concept and experimentation through launch, product-market fit, adoption, and scale, remaining accountable for customer and business outcomes beyond the initial release. Navigate the introduction of a new AI-driven product paradigm alongside an established platform, considering customer migration, adoption barriers, potential cannibalization, and long-term product strategy. Develop a deep understanding of proposal and response workflows, including RFPs, security questionnaires, and DDQs, and engage directly with customers and prospects to identify opportunities and validate product direction. Monitor the competitive and market landscape for agentic automation and translate emerging trends into actionable product opportunities. Build alignment and enthusiasm across executives, cross-functional stakeholders, customers, and delivery teams by communicating product vision, progress, priorities, and performance metrics clearly. Operate as an internal thought leader on agentic product design, product discovery, prioritization, experimentation, and responsible AI adoption. Use AI tools extensively across research, prototyping, product specifications, artifact creation, and other aspects of the product management lifecycle. Identify opportunities independently, rally the right people around them, and maintain a strong bias toward shipping, learning, and measurable results. Requirements Proven track record of building and launching new products, achieving product-market fit, and driving meaningful adoption, preferably within or alongside an established product. Direct experience developing agentic or AI-powered experiences in a B2B SaaS environment; experience with enterprise workflows, sales technology, or proposal/RFP automation is an advantage. Strong working knowledge of LLMs, agent orchestration, RAG pipelines, model selection, context windows, latency, reliability, an
This page is generated from the committed OpenOpps static snapshot. Use the source posting or apply link for the employer's current canonical posting state.