Our world is transforming, and PTC is leading the way. Our software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business.
Our people make all the difference in our success. Today, we are a global team of nearly 7,000 and our main objective is to create opportunities for our team members to explore, learn, and grow – all while seeing their ideas come to life and celebrating the differences that make us who we are and the work we do possible.
Senior Director, Enterprise Intelligence
Information Technology | Data, Analytics, AI & Automation | Boston, MA (Hybrid)
Overview
PTC is building one governed data foundation and an AI-native operating model on top of it. As Senior Director, Enterprise Intelligence, you will build both, run them, and make data and AI a measurable part of how PTC works.
About the Role
IT's vision is one PTC running on one modern, secure, AI-native technology core. This role owns the intelligence in that core: data the company can trust, and AI and automation that use it to free up time in Finance, Sales, Marketing, Customer Success, HR and IT itself. One leader owns both, so AI is never built on data that is not ready for it.
PTC is investing in AI and is now focused on putting it to work at scale. Tools are spread across functions, the AI Center of Excellence and the BI team sit outside IT, and there is not yet a single data platform, semantic layer or metric definition. Adoption, not access, is now the constraint.
PTC builds the software that runs the world's product companies. We want a leader who will treat PTC as its own Customer Zero, proving data and AI capabilities on our own processes and products before our customers rely on them.
What You Will Own
Strategy and Adoption
Set PTC's enterprise data, analytics and AI strategy and roadmap with the CIO, tied to business outcomes rather than tool counts, and sequence it so the data foundation is never held back while AI moves ahead.
Run AI adoption across Finance, Sales/GTM, Marketing, Customer Support & Success, HR and IT, with use cases chosen alongside business leaders and measured in hours and cycle time returned.
Rationalize the AI, data and BI tool estate, consolidating overlapping copilots, assistants, reporting tools and platforms into a governed, funded set.
Data Foundation and Analytics
Own the enterprise data platform and data engineering roadmap, moving fragmented data and reporting tools onto one platform.
Build and run a single semantic and metrics layer, so each business metric has one definition, one owner and one source of truth.
Lead Analytics & BI, bringing report and dashboard development from across the business into one accountable team with clear service levels.
Establish data governance, quality and stewardship: named owners for critical data domains, automated quality monitoring and remediation, and lineage for regulated and financial data.
Run data as a product, with a named consumer, roadmap and service level for each.
Build and Run AI
Stand up an agent factory: a repeatable way to design, build, test, release and operate AI agents and automations.
Architect AI-ready platforms, including RAG, agentic workflows, event-driven integration and secure APIs, with Enterprise Architecture.
Own agent operations, so that every agent in production is registered, owned, monitored and auditable.
Partner with Digital Workplace on an autonomous, agentic service desk and AI-led employee self-service.
Embed AI in core business platforms, including Salesforce-based Lead-to-Order and Quote-to-Cash, with Global Enterprise Engineering.
Govern and Secure
Chair the Data & AI Council with Enterprise Architecture and the CISO, and apply AI guardrails: identity and least-privilege access for agents, data governance, model risk and auditability.
Enforce the autonomy rule: agents may act autonomously only within guardrails, and never on an…