Senior Product Manager, Integration Ecosystem

About Enterpret

As the world moves to AI native applications, one element matters more than anything: the data. At Enterpret, we are unlocking the most impactful dataset for businesses, customer feedback. We centralize feedback across every source, like Twitter, Salesforce, Zendesk, Slack, Intercom, community forums, surveys, and Gong calls, into a single context graph. On top of it we build an adaptive taxonomy for each customer and an agent platform that lets teams query, monitor, and act on customer intelligence wherever they work, whether that's inside Enterpret, in Slack, or in their own AI tools through our MCP server.

Our customers include companies like Canva, Notion, WisprFlow, ElevenLabs, OpenRouter, Western Union, and several other Product Led Growth decacorns and F500 companies. We are backed by Kleiner Perkins, Peak XV Partners, and Unusual Ventures.

Our engineering culture is AI-native from the ground up. Agents, LLMs, and applied ML are not a side project here, they are the core of how we build. We work at the edge of what is possible in agentic systems and push past it.

About the Role

Every record in Enterpret's context graph arrives through an integration. We ingest customer context from fifty plus sources, and from our customers' own systems through our ingestion API.

This surface decides how accurate, complete, and fresh everything downstream is. It has been engineering-led so far. You will be the first product manager for the Integration Ecosystem, working with a dedicated engineering team and reporting into the product organization. You own two things: the experience of setting up and managing integrations, and the behavior of the system underneath.

You will think from first principles about how an enterprise's customer context should reach Enterpret, and build a cohesive ingestion layer on top of the integrations we already have.

What You Will Do

Run the fleet like a portfolio. Fifty integrations, each built on a platform whose APIs, data models, and conventions keep moving. You will prioritize by revenue impact and error frequency, put the hard calls in writing, and decide which platforms the ecosystem integrates with next.

Own the system-behavior metrics for ingestion: completeness, latency, and error rates. You will define them, instrument them, and be measured on them.

Own the integration setup and management experience end to end: connecting a source, scoping exactly what gets ingested (filters, backfill windows, previews), and managing it over time.

Define per-integration error taxonomies, decide which failures customers see and which page our team, and ship proactive notifications so customers hear about issues from us first.

Build agent-first setup: an agent inspects the customer's source, proposes the right configuration, and the customer reviews and confirms. You decide where a form still earns its place.

What It Takes

Direct product ownership of integrations, connectors, data ingestion, or API products on technical B2B surfaces. You have carried them through real platform change, like API deprecations, auth migrations, and breaking version upgrades.

Fluency in how platform APIs actually behave — auth flows, webhooks, rate limits, pagination, deprecation cycles — enough to hold your own in trade-off debates with engineers.

You have defined reliability and experience metrics where none existed, instrumented them, and moved them.

Comfort operating AI-first. Our default is that not using AI for a task is the choice that needs explaining.

What Success Looks Like

In 3 months: You own the problem inventory for the integration ecosystem, prioritized by revenue and error frequency. The highest-usage integration has a complete error taxonomy, and it is the template the rest of the fleet follows. Baselines exist for completeness, latency, and error rates.

In 6 months: Setup is self-serve for the majority of sources. Customers resolve the most common issues themsel …