Engagement Manager - Data as a Service

About the Team

The Data-as-a-Service Engagement Management team sits at the center of Snorkel AI's DaaS business, partnering with leading AI labs and enterprises to deliver high-quality datasets that power frontier AI systems. The team drives customer adoption, consumption, and expansion, working closely with Sales, Delivery, Product, and Engineering. This role reports to the Head of Engagement Management, DaaS.

About the Role

This is a founding Engagement Manager role, built around depth rather than breadth. You will own a small number of strategic frontier-lab and enterprise accounts, each running many projects at once. You own revenue and customer value on those accounts, keeping delivery aligned to agreed upon specifications, and making sure delivered work gets accepted and becomes recognized revenue.

Your main focus is post-sales: keeping deliveries on track and acting as the main point of contact for Sales across everything happening on the account. An Account Executive comes to you for the whole picture rather than tracking down a different Technical Delivery Manager for each project. You also stay close to deals in pre-sales and pipeline, since new opportunities arrive constantly and you and the Account Executive share the account throughout its life.

As a founding hire, you will help define what Engagement Management becomes at Snorkel. The playbooks, escalation paths, and operating cadence you build here are what the function will run on as it grows, including the responsibilities and handoffs between Engagement Management, Sales, and Delivery.

About You

You have been an early customer-facing owner at a company where the motion did not exist yet. You are comfortable when the structure is still being defined, and you would rather build the operating rhythm than inherit one. You get more energy from going deep on a hard technical account than from covering a wide portfolio.

You have owned accounts with significant revenue and seen a well-run delivery operation up close, so you know what good looks like: what a healthy program looks like week to week, which early signals mean trouble, and what to fix first when several things are wrong at once.

You can hold a working conversation with ML researchers about evaluation criteria, data quality, and what makes a specification precise enough to build against, without pretending to be a researcher yourself. When a customer changes what they want mid-delivery, you can separate a defect from a preference from a genuine change in scope, and hold that line commercially without damaging the relationship.

Responsibilities

• Own post-sale outcomes for your accounts: adoption, consumption, and revenue realization
• Turn broad customer commitments into a clear, actively managed set of data orders with agreed sequencing and timing
• Coordinate delivery across many concurrent projects and phases, maintaining a single view of scope, risk, ownership, and next steps
• Own the customer conversation when specification or scope changes mid-delivery, working from the Technical Delivery Manager's classification of defect, preference, or change order
• Ensure delivered datasets convert into recognized revenue on the expected timeline
• Build deep, multi-threaded relationships across technical, research, operational, and executive stakeholders
• Partner with the Account Executive on account strategy, the next-order roadmap, and expansion
• Surface risks early enough that it does not arrive as an executive escalation
• Codify what works into playbooks, escalation paths, and operating cadences the wider EM function will adopt

Requirements

• 5+ years in customer success, engagement management, account management, or technical consulting in a data-driven or technical environment
• Experience as a founding or early customer-facing owner who built the customer motion at a company rather than inheriting one. We will ask what you built and what you deliberately chose not to build
• Experience owning accounts with significant revenue, and a clear point of view on what good looks like and how you measured it
• Demonstrated experience managing scope or specification change with a customer during active delivery, not only handling escalations after the fact
• Track record of driving adoption, consumption, and expansion in complex enterprise accounts
• Experience in a shared ownership model with Sales or Account Executives
• Ability to hold a substantive conversation with technical and research stakeholders about data quality, evaluation, and specification precision
• Comfort operating with ambiguity, competing priorities, and a fast-changing set of facts
• Willingness to travel based on customer needs

Bonus points for

• Experience working with frontier AI labs or research organizations
• Experience with AI/ML workflows, data annotation, evaluation, or data infrastructure
• Experience owning revenue recognized against delivered and accepted work, rather than seat- or subscription-based renewal
• Experience as the first hire into a function that later scaled

This role is hybrid 3 days in office in San Francisco, CA or New York, NY.