Senior Director, Enterprise Intelligence

Pilot Thomas Logistics•Boston, MA

1d•Hybrid

About The Position

PTC is seeking a Senior Director, Enterprise Intelligence to build and lead its enterprise data foundation and AI-native operating model. The role owns trusted enterprise data, analytics, AI, and automation, with the goal of making these capabilities measurable contributors to how PTC operates. Working with the CIO and business leaders, the role sets strategy and roadmaps tied to business outcomes and ensures AI adoption is built on governed, reliable data. The Senior Director will consolidate fragmented data, analytics, BI, and AI tools; establish an enterprise data platform and a shared semantic and metrics layer; and lead analytics and BI as an accountable function. The role will develop data governance, quality, stewardship, and product practices, and establish an agent factory and operating controls for production AI agents and automations. It will partner with Enterprise Architecture, the CISO, Digital Workplace, and Global Enterprise Engineering to build and secure AI capabilities, including AI-enabled employee services and AI embedded in business platforms. The role also builds the organization by bringing the AI Center of Excellence and BI team into IT, hiring data and AI engineering leaders, and embedding AI Enablement Leads across IT. As PTC’s Customer Zero leader, it will apply PTC products and AI capabilities to PTC’s own operations and feed lessons back to Product & Engineering. The position is based in Boston, Massachusetts, with a hybrid arrangement requiring two days per week in the office. The annual base salary range is $225,000 to $315,000. The position is not eligible for employment-based immigration sponsorship; applicants must be authorized to work in the United States without current or future sponsorship.

Requirements

15+ years in enterprise technology, data, or engineering.
7+ years leading large, multi-site teams and managing leaders of leaders.
Track record consolidating fragmented data and BI estates onto a modern cloud data platform with a semantic layer, and operating enterprise-scale data governance and quality.
Track record driving enterprise AI strategy and adoption across multiple business functions, with production results measured in hours saved, requests automated, or cycle time reduced.
Hands-on depth in GenAI, RAG, and agentic AI systems, with judgment to take them from pilot to governed production.
Experience building an organization from the ground up, including hiring leaders, setting culture, and scaling globally.
Architecture strength 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 turn priorities into roadmaps and investment decisions.
Bachelor’s degree in Computer Science, a quantitative field, or equivalent experience.
Must be authorized to work in the United States without requiring current or future employment-based immigration sponsorship.

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, including Administrator or Developer certification.
Microsoft Azure certification, such as Data Engineer, Developer, or equivalent.
ITIL and Scrum/agile certification or equivalent practice.
Experience leading teams across India, the United States, and Europe.

Responsibilities

Set PTC’s enterprise data, analytics, and AI strategy and roadmap with the CIO, tied to business outcomes and sequenced so the data foundation keeps pace with AI.
Lead AI adoption across Finance, Sales/GTM, Marketing, Customer Support & Success, HR, and IT, selecting use cases with business leaders and measuring productivity in hours and cycle time returned.
Rationalize and consolidate overlapping AI, data, BI, reporting, copilot, assistant, and platform tools into a governed and funded portfolio.
Own the enterprise data platform and data engineering roadmap, consolidating fragmented data and reporting tools onto one platform.
Build and operate a shared semantic and metrics layer with a single 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 data governance, quality, and stewardship, including named owners for critical data domains, automated quality 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: a repeatable process for designing, building, testing, releasing, and operating AI agents and automations.
Architect AI-ready platforms, including RAG, agentic workflows, event-driven integration, and secure APIs, in partnership with Enterprise Architecture.
Own agent operations so 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, and apply AI guardrails covering identity, 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 moving the AI Center of Excellence and BI team into IT, hiring data and analytics and AI engineering leads, and embedding AI Enablement Leads in every IT function.
Champion Customer Zero by using PTC’s own products and AI capabilities internally and sharing lessons with Product & Engineering.
Own the Intelligence metric for the CIO’s scorecard, spanning data and AI.
Deliver first-year outcomes including a unified data platform, semantic layer and ELT metric definitions; named owners for critical data domains; trusted data and consolidated BI tools; at least 20% productivity gain in priority processes through AI; at least 50% of service requests resolved without human touch in partnership with Digital Workplace; a production agent in every business domain; a governed, consolidated AI estate; and the AI Center of Excellence and BI team integrated into IT.