Senior Director, Enterprise Intelligence

PTC•Boston, MA

2d•$225,000 - $315,000•Hybrid

About The Position

PTC is seeking a Senior Director, Enterprise Intelligence to build and operate a governed enterprise data foundation and an AI-native operating model. The role owns enterprise data, analytics, AI and automation, ensuring that AI is built on trusted data and delivers measurable business outcomes. The position is part of Information Technology and is based in Boston, Massachusetts, on a hybrid schedule with two days per week in the office. The Senior Director will set PTC’s enterprise data, analytics and AI strategy with the CIO; drive adoption across Finance, Sales/GTM, Marketing, Customer Support and Success, HR, and IT; and rationalize the company’s AI, data and BI tools. The role will own the enterprise data platform, data engineering roadmap, semantic and metrics layer, Analytics & BI function, data governance, quality, stewardship, and data-as-a-product practices. The role will establish a repeatable AI agent development and operations capability, architect AI-ready platforms and integrations, and embed AI in core business platforms and employee services. It will chair the Data & AI Council with Enterprise Architecture and the CISO, enforce security and governance guardrails, and ensure agents do not perform irreversible actions without human approval. The leader will bring the AI Center of Excellence and BI team into IT, build the organization and leadership team, embed AI Enablement Leads across IT, and champion PTC as its own Customer Zero. First-year objectives include establishing one data platform, semantic layer and definition for ELT-reviewed metrics; improving trusted data and consolidating BI tools; achieving at least a 20% productivity gain in priority processes through AI; resolving at least 50% of service requests without human intervention in partnership with Digital Workplace; putting an agent factory and production agents into each business domain; governing AI and data spend through one portfolio; and integrating the AI Center of Excellence and BI team into IT.

Requirements

15 or more years of experience in enterprise technology, data or engineering.
At least 7 years leading large, multi-site teams and managing leaders of leaders.
Demonstrated success consolidating fragmented data and BI environments onto a modern cloud data platform with a semantic layer, and operating enterprise-scale data governance and quality.
Demonstrated success leading enterprise AI strategy and adoption across multiple business functions, with production outcomes measured in hours saved, requests automated or cycle time reduced.
Hands-on depth in GenAI, RAG and agentic AI systems, and the judgment to take them from pilot into governed production.
Experience building an organization from the ground up, including hiring leaders, establishing culture and scaling globally.
Strong architecture experience across cloud-native and hybrid platforms, distributed and event-driven systems, APIs and enterprise integration.
Experience embedding security and governance, including IAM/RBAC, least-privilege access, auditability, data privacy and data governance across enterprise applications.
Experience partnering with a CIO, CFO and business leaders to translate priorities into roadmaps and investment decisions.
Bachelor’s degree in Computer Science, a quantitative field, or equivalent experience.

Nice To Haves

Experience at a software product company, including running a Customer Zero program.
Experience building customer-facing SaaS products as well as internal enterprise platforms.
Experience with subscription, ARR and go-to-market data.
Salesforce platform expertise or Administrator/Developer certification.
Microsoft Azure certification in Data Engineering, Development or equivalent.
ITIL and Scrum/agile certification or equivalent practice.
Experience leading teams across India, the United States and Europe.

Responsibilities

Set the enterprise data, analytics and AI strategy and roadmap with the CIO, tying priorities to business outcomes and sequencing foundational data work alongside AI adoption.
Drive AI adoption across Finance, Sales/GTM, Marketing, Customer Support and Success, HR, and IT, selecting use cases with business leaders and measuring productivity and cycle-time results.
Rationalize and consolidate overlapping AI, data, BI, reporting, assistant and platform tools into a governed, funded portfolio.
Own the enterprise data platform and data engineering roadmap, moving fragmented data and reporting tools onto one platform.
Build and operate a single semantic and metrics layer with one definition, owner and source of truth for each business metric.
Lead Analytics & BI and consolidate report and dashboard development into one accountable team with clear service levels.
Establish enterprise data governance, quality and stewardship, including named owners for critical domains, automated monitoring and remediation, and lineage for regulated and financial data.
Manage data as a product, with a named consumer, roadmap and service level for each data product.
Establish an agent factory for repeatable design, development, testing, release and operation of AI agents and automations.
Architect AI-ready platforms and systems, including RAG, agentic workflows, event-driven integration and secure APIs, in partnership with Enterprise Architecture.
Own agent operations, ensuring every production agent 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.
Chair the Data & AI Council with Enterprise Architecture and the CISO, applying guardrails for agent identity and least-privilege access, data governance, model risk and auditability.
Ensure agents act autonomously only within guardrails and require human approval before irreversible actions.
Build the function by bringing the AI Center of Excellence and BI team into IT, hiring data and analytics and AI engineering leads, and placing AI Enablement Leads within every IT function.
Champion Customer Zero by using PTC products and AI capabilities internally first and sharing lessons with Product & Engineering.
Own the Intelligence metric on the CIO’s scorecard, spanning data and AI.