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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Product Manager, Applied AI & Data Science - **Company:** Autodesk - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $123,900 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Data Analysis, Confluence, JIRA, Information Engineering, Document Management Systems, Machine Learning, Azure Machine Learning, Enterprise Software Applications, Wikis, Data Management, Autodesk Autocad, Data Pipelines, Airtable - **Published:** November 7, 2026 - **Apply:** https://dejobs.org/x/x/F38D80F2993D4A3593D3B572729E2A8E/job/ ## About the Role * 8+ years of product management experience, including experience owning roadmaps for data, analytics, or AI/ML platform products * Strong fluency in data and AI concepts - semantic data models, data pipelines, and machine learning / generative AI applications - sufficient to partner credibly with engineering and data science * Proven experience partnering with engineering, data science, architecture, and governance teams to scope and deliver complex, cross-functional initiatives * Excellent written and verbal communication skills, including experience presenting roadmaps, trade-offs, and business impact to executive stakeholders * Hands-on experience with product and delivery tooling such as Jira, Airtable, and Confluence/Wiki * Bachelor's degree in a related field, or equivalent practical experience ## Description We are seeking a Principal Product Manager for the Applied AI, Data Science, and Data Engineering team within the Enterprise Systems and Experience (ESE) organization. This team owns and operates the enterprise data foundation that ESE builds on - semantic data models, AI-ready data products, and the agents and automations that reason across that data to drive workforce productivity. This team's mandate is to build scalable, reusable products that deliver lasting value. This Principal PM will bring product discipline to a fast-growing portfolio: clear roadmaps, sharp prioritization, and consistent delivery of measurable, visible outcomes to stakeholders across the company. Responsibilities * Translate strategy into detailed product roadmaps, execution plans, milestones, and measurable outcomes * Own roadmap development and prioritization across the enterprise data hub, AI-ready data products, self-service conversational analytics, data-as-a-service capabilities, bring-your-own-data capabilities, semantic data models, and AI value realization initiatives * Bring strong fluency in data, analytics, and AI, and apply it to help define dashboards and reporting as data and AI products * Make and defend prioritization decisions and communicate those decisions clearly to engineering and stakeholder teams * Lead intake, discovery, and backlog refinement across a high volume of stakeholder requests, with a consistent lens on what delivers the most value to the broadest set of users * Convert business needs into clear product requirements documents, user stories, acceptance criteria, business value statements, and delivery milestones * Partner with engineering, data science, applied AI, architecture, governance, and business stakeholders to ensure roadmap items are clearly scoped, sequenced, and delivered * Track roadmap progress, risks, dependencies, blockers, decisions, and stakeholder commitments to maintain delivery alignment * Drive adoption and product health measurement, including usage, reuse, data quality, freshness, stakeholder satisfaction, and realized business value * Support executive communication through concise roadmap updates, delivery status, trade-off decisions, and business impact summaries * Maintain alignment across Airtable, Jira, Wiki, and related planning and documentation systems * Shift the team's delivery model from reactive, request-by-request execution to a scalable portfolio of reusable, governed AI and data products that Autodesk owns outright * Define and evolve the product vision and strategy for enterprise AI and data products, connecting business and user needs, technology capabilities, and company priorities into a clear set of product bets and investment choices. * Lead product discovery to deeply understand user problems, workflows, unmet needs, and opportunities; distinguish underlying customer problems from requested solutions and use evidence to determine what the team should - and should not - build. * Develop a portfolio strategy that identifies common needs across teams and translates them into scalable, reusable platform capabilities rather than one-off solutions for individual stakeholders. * Establish clear product hypotheses, target users, value propositions, success measures, and expected business outcomes before committing significant investment; use qualitative and quantitative evidence to validate assumptions and guide continued investment. (Capacity planning with ENG teams) * Own product lifecycle decisions from discovery and incubation through launch, adoption, iteration, scaling, and retirement, using product health and realized value to determine where to expand, pivot, consolidate, or stop investment. * Exercise strong product judgment in ambiguous environments , balancing user value, business impact, technical feasibility, platform leverage, risk, and opportunity cost to make and communicate difficult investment and prioritization decisions.