Senior Product Manager, Construction AI

** Job

Requisition  #*
* 26WD98284

** Position Overview*
* As a Senior Product Manager, Construction AI, you will lead a portfolio of AI assistant workflows across Autodesk Construction Cloud. You will work at the intersection of construction domain expertise, AI/ML capabilities, customer workflows, platform services, and product execution. You will be responsible for identifying the highest-value customer problems, shaping product strategy, defining requirements, prioritizing roadmap investments, and partnering with engineering, design, data science, research, legal, trust, GTM, and customer-facing teams to deliver trusted AI experiences s is a high-ambiguity, high-impact role for someone who can translate construction workflows into AI product opportunities, balance innovation with responsible AI practices, and drive execution across complex cross-functional teams.

** Responsibilities*
* + 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…