Senior Product Manager

Pendo•Raleigh, NC

5d•$150,000 - $175,000•Hybrid

About The Position

The team builds the tools that help software teams understand how their products are used, where adoption breaks down, and what drives business outcomes. AI features are increasingly central to the analytics roadmap — surfacing intelligent insights, automating pattern detection, and embedding AI-assisted workflows directly into the product experience. This team is embedded in its own customer base, runs continuous discovery, and treats customer outcomes as the primary measure of whether the work is good. This role owns an analytics product area end-to-end: strategy, roadmap, discovery, and delivery across a globally distributed cross-functional team spanning Raleigh, New York, and Pendo's India-based engineering and product teams. Customer outcomes are the starting point for every significant decision. Discovery is continuous, not episodic. Operating across time zones is a practical requirement — the person in this role adapts their working hours to maintain meaningful overlap with India-based teams and builds the async artifacts that let those teams work independently between overlap windows. This role is based in Raleigh, NC (primary), with New York, NY and East Coast remote candidates also considered. Pendo's hybrid model requires in-office 3 days per week for local candidates.

Requirements

5+ years of product management experience with a track record of owning product areas end-to-end in a B2B SaaS environment.
Experience defining or shipping AI-powered product features — you can work with engineering to spec what a model does, how outputs are surfaced, how confidence is communicated, and where human judgment stays in the loop.
Demonstrated experience building for enterprise customers, including navigating complex procurement, security, compliance, or data privacy requirements.
Experience using AI prototyping or code generation tools (Cursor, v0, Replit, GitHub Copilot, or similar) to validate product ideas before engineering investment; specific examples of AI use in daily workflows are expected in the interview process.
Experience taking a product or major feature through the full lifecycle — scoping, sequencing, launching, and iterating — and making scope and sequence calls without consensus.
A track record of running toward customers: maintaining direct relationships with enterprise customers, treating discovery as ongoing rather than project-scoped, and pointing to specific conversations that changed a product decision.
Experience working with or within globally distributed teams, with async-first communication practices; written specs and updates leave no open questions.

Nice To Haves

Background in analytics products, data visualization, or data platform work in a B2B context.
Familiarity with Pendo as a user or customer.
Prior experience working with India-based engineering or product teams.

Responsibilities

Own the analytics product roadmap — define priorities, defend tradeoffs with data and reasoning, and keep the long-term direction aligned with enterprise customer needs and the broader Pendo platform.
Drive AI-powered capabilities within the analytics area: define what the AI does, how outputs are surfaced, how confidence is communicated, and where human judgment stays in the loop — with the customer problem as the starting point, not the model capability.
Run continuous discovery with enterprise customers and India-based product and engineering teams; synthesize findings across time zones into clear, actionable product decisions without requiring a synchronous handoff.
Lead the full product lifecycle for the analytics area from early concept through GA and post-launch iteration; make clear calls on scope, sequence, and tradeoffs and own the outcome.
Apply AI tools across the full product cycle — synthesizing discovery at scale, generating early wireframe concepts, drafting specs and competitive analyses — and share methods and findings with the broader product team.
Serve as the subject-matter expert for Sales, Customer Success, Marketing, and Partnerships on the analytics area; translate product capability into commercial narrative and feed market signal back into the roadmap.
Write specs that engineering can act on without a verbal walkthrough; document decisions, produce async artifacts that reduce synchronous dependency, and bring a substantive point of view to design reviews.