Head of Enterprise Productivity

Chubb•New York, NY

50d

About The Position

We are seeking a visionary Head of AI Platform Product to lead the strategy and expansion of Chubb's centralized Intelligent Productivity Platform. You will own the roadmap for the enterprise-wide "operating system" for Generative AI-the unified hub where thousands of employees interact with advanced models, utilize specialized skills, and automate their daily workflows. This is not a consulting role; it is a software product leadership role. You will treat the global organization as your customer base. Your mission is to lead the engineering and product teams to scale this platform into a robust, intuitive, and feature-rich environment that drives measurable productivity gains across the entire company. You will ensure our workforce has secure, seamless access to the best-in-class AI capabilities they need to work smarter, not harder.

Requirements

15+ years of progressive experience in Technology Leadership, Product Management, or Software Engineering.
5+ years of specific experience leading Software Product Development (owning the roadmap and growth of live platforms or applications).
Masters, PhD, or equivalent experience in a quantitative or technical field (Computer Science, Engineering, Artificial Intelligence, Data Science).

Nice To Haves

Proven Track Record: Demonstrated success in scaling software products, developer platforms, or enterprise tools from initial launch to widespread adoption.
Experience working in a regulated industry (Insurance, Finance, Healthcare) is preferred but not required; a strong background in B2B SaaS or Enterprise Software is highly valued.

Responsibilities

Enterprise Product Strategy: Own the vision. Treat the internal platform as a Tier-1 software product. Analyze the "market" (our employee base) to identify broad user needs and scale solutions that serve the many, not the few. Move beyond bespoke, one-off projects to build scalable features that lift the entire enterprise.
Lead Platform Development: Lead the agile product and engineering teams to drive the continuous evolution of the platform. Manage the roadmap to balance rapid feature delivery (e.g., new model integrations, advanced data analysis tools) with enterprise-grade stability and security.
User Experience & Product-Led Growth: Obsess over the user journey. Ensure the platform is as intuitive and frictionless as consumer-grade software. Drive adoption not just through mandates, but by building a tool so useful that employees delight in using it.
Capability Ecosystem: Oversee the expansion of the platform's "skills" library. Design the architecture that allows the platform to securely ingest company knowledge and execute specialized tasks, ensuring the tool evolves from a passive assistant to an active productivity engine.
Value & Analytics: Define success metrics (DAU/MAU, task completion rates, time-savings). Use product analytics to understand how employees are using the tool, identify friction points, and iterate on features to maximize ROI.
Innovation & Integration: Stay at the bleeding edge of the GenAI landscape. Determine which new external models or technologies should be integrated into the platform to maintain its competitive advantage, while masking the complexity for the end-user.
SaaS/Product Mindset: Expert-level knowledge of managing software products at scale. You understand how to build features that solve problems for a broad user base rather than hard-coding solutions for specific individuals.
Generative AI Fluency: Deep understanding of the GenAI stack-LLMs, RAG (Retrieval-Augmented Generation), and Agentic workflows. You understand the "art of the possible" and how to productize these technologies into a simple user interface.
Engineering Leadership: Significant experience working alongside software engineers. You can speak the language of the builders (Python, React, Cloud Infrastructure, API design) to guide architectural trade-offs and technical strategy.
Platform Architecture: Strong understanding of how to architect scalable, secure internal platforms. Knowledge of microservices and containerization to ensure the platform can handle high concurrency and complex data integrations.
Data-Driven: Ability to use quantitative data to defend roadmap decisions and qualitative feedback to refine the user experience.