• Define and own the product vision, strategy, and roadmap for Construction AI assistant workflows across Autodesk Construction Cloud • Translate customer pain points, market signals, AI capabilities, and business priorities into a clear, sequenced roadmap • Prioritize opportunities across answer-finding, project intelligence, workflow automation, document understanding, drawing/model interactions, and agentic actions • Identify where AI can create differentiated customer value versus where deterministic workflow, rules, UX, or platform improvements are more appropriate • Partner with product leadership to align Construction AI investments with Autodesk’s broader platform, data, and AI strategy • Develop deep understanding of construction personas, including project managers, superintendents, VDC/BIM teams, project engineers, estimators, document controllers, account/project admins, and executives • Conduct customer discovery to identify workflows where AI can reduce search time, rework, risk, delay, and administrative burden • Build fluency in construction documents and workflows such as RFIs, submittals, specifications, issues, meetings, schedules, drawings, models, change orders, and project administration • Monitor construction technology, AI assistant, agentic workflow, and construction automation trends to identify opportunities and competitive threats • Represent the voice of the customer in product, engineering, data science, and executive discussions • Partner closely with engineering, data science, design, and architecture teams to define AI-powered assistant experiences from concept through launch • Write clear product requirements, user stories, success criteria, model behavior expectations, and acceptance criteria for AI workflows • Collaborate on AI evaluation methods, prompt and agent behavior, retrieval quality, grounding, permissions, observability, and model performance • Ensure AI experiences are useful in real construction practice, not merely technically correct • Define product requirements for responsible AI, including transparency, user control, provenance, escalation paths, quality thresholds, and human-in-the-loop review • Work with platform and data teams to leverage construction knowledge graphs, project context, permissions, and workflow data to improve assistant quality and trust • Lead cross-functional product execution from discovery through beta, GA, adoption, and iteration • Make difficult roadmap tradeoffs using customer impact, technical feasibility, AI readiness, business value, risk, cost, and adoption data • Partner with design to create intuitive assistant and automation experiences embedded directly into customer workflows • Partner with engineering to manage dependencies, sequencing, release planning, technical constraints, and operational readiness • Partner with Trust, Legal, Privacy, Security, and Responsible AI teams to ensure AI capabilities meet Autodesk standards and customer expectations • Drive product launches in partnership with Product Marketing, Sales, Customer Success, Support, Enablement, and field teams • Define success metrics for AI assistant workflows, including adoption, task completion, answer quality, automation success, time saved, customer satisfaction, trust, retention, and business impact • Use product analytics, customer feedback, model evaluation, support signals, and field input to guide roadmap decisions • Establish feedback loops that continuously improve AI quality, usability, and workflow relevance • Communicate product performance, roadmap progress, risks, and tradeoffs clearly to stakeholders and senior leaders • Establish a clear, compelling roadmap for Construction AI assistant workflows • Build alignment across product, engineering, data science, design, GTM, and leadership • Deliver measurable progress on one or more high-value assistant or agentic workflow areas • Improve clarity around where AI should answer, recommend, automate, or defer to a human • Define repeatable product patterns for trusted AI workflows in construction • Increase customer confidence, usage, and adoption of Autodesk’s Construction AI portfolio.

• Prioritize work based on alignment to business priorities, cost, and expected return on investment; clearly articulate tradeoffs behind every call • Build and measure iteratively, shipping in increments and using success metric results to determine what's next – pivot or stay the course • Communicate clearly and often about what we’re building, why it's the most important thing to do, and how we will know if it worked • Use data to make decisions – from customer adoption analytics to competitor and market intelligence – know how to cut through the noise to find signal • Collaborate relentlessly with other product managers, design, engineering and go-to-market teams to release new value with speed. • Leverage AI-powered workflows to drive efficiency, reducing time-to-validation while delivering innovative solutions.

• Own the platform’s core surfaces end-to-end, including onboarding, permissions, preferences, homepage, notifications, audit trail, and reporting, from strategy through iteration. • Champion the end-to-end user experience, map real user flows and journeys, and shape intuitive, cohesive interactions across every surface. • Think in systems to design primitives and patterns that compose cleanly across products, anticipating second-order effects and prioritizing long-term foundations. • Turn messy, ambiguous horizontal challenges into concrete, elegant requirements and shipped software. • Establish direction with data, defining clear success metrics and leveraging analytics to guide future iteration. • Leverage the latest AI prototyping tools to pressure-test ideas and build rapid proofs-of-concept before committing engineering time. • Facilitate airtight coordination across engineering, design, data, and GTM functions to ship cohesive products.

• Own the backlog and story quality for a complex engagement — often spanning multiple engineering tracks or workstreams • Translate product strategy and roadmap from a 3Pillar PM or client PM into epics, stories, and acceptance criteria with a high degree of independence • Navigate ambiguity confidently: identify gaps in requirements, drive the right conversations to resolve them, and make well-reasoned decisions when direction is incomplete • Lead and facilitate backlog refinement sessions; ensure the team is never blocked waiting on story clarity • Actively participate in all Agile ceremonies as a senior, prepared contributor — and help shape ceremony effectiveness • Mentor and guide POs on the engagement; review their stories, raise the quality bar, and invest in their development • Partner with UX to ensure research findings and design decisions are translated faithfully and completely into the backlog • Communicate backlog health, scope risks, and delivery signals clearly to the PM and Delivery Lead • Champion AI-forward backlog practices — model effective use of AI in story writing, acceptance criteria, and requirements analysis; help the team adopt these habits • Contribute product context in client-facing sessions when needed — credible and clear on scope, requirements, and trade-offs