Engagement Manager - Data as a Service

Snorkel AI•Redwood City, CA

14h•Remote

About The Position

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Team The Data-as-a-Service Engagement Management team sits at the center of Snorkel AI’s DssS business, partnering with leading AI labs and enterprises to deliver high-quality datasets that power frontier AI systems, and reports into the GM of the business. The team is responsible for driving customer adoption, consumption, and expansion, working closely with Sales, Delivery, Product, and Engineering. About the Role As an Engagement Manager, DaaS, you will own customer outcomes and revenue realization across your accounts. You are responsible for driving consumption of DaaS offerings and ensuring booked revenue is recognized. You will serve as the primary point of contact for enterprise customers, building strong relationships and guiding them from pilot through production. In close partnership with Account Executives, you will drive expansion and long-term account growth. This role blends customer success, commercial partnership, and delivery oversight—you are accountable for both successful delivery and sustained customer value. About You You are a customer-focused operator with strong ownership over outcomes. You’re comfortable managing complex accounts, navigating ambiguity, and working cross-functionally to drive both customer success and business growth. You bring experience working with enterprise customers in technical or data-driven environments and are motivated by building long-term, high-impact partnerships.

Requirements

5+ years of experience in customer success, account management, consulting, or a related post-sales role in a technical or data-driven environment
Excellent track record of managing enterprise accounts and driving customer adoption, consumption, and expansion
Experience partnering closely with Sales or Account Executives in a shared ownership model of account growth
Strong ability to manage complex delivery programs while maintaining focus on customer outcomes and business impact
Excellent communication and interpersonal skills, with the ability to engage both technical and non-technical stakeholders
Technical aptitude in data, AI/ML, or related domains
Ability to navigate ambiguity, solve problems proactively, and operate effectively in a fast-paced environment
Familiarity with usage-based or consumption-driven business models
Willingness to travel up to 20% based on customer needs

Nice To Haves

Experience working with AI/ML workflows, data annotation, or data infrastructure
Experience driving net revenue retention (NRR) or expansion metrics in enterprise accounts

Responsibilities

Own post-sale customer outcomes, including adoption, consumption, and revenue realization across assigned DaaS accounts
Drive ongoing consumption of contracted datasets, ensuring bookings are converted into recognized revenue
Build deep, multi-threaded relationships across customer organizations, including technical, operational, and executive stakeholders
Partner closely with Account Executives to identify, shape, and progress expansion opportunities
Lead customer engagements from project kick-off through ongoing production, ensuring alignment on goals, timelines, and success criteria
Manage delivery of complex datasets with the Delivery team, meeting quality, scope, and SLA expectations while proactively identifying risks
Communicate value delivered, usage trends, and growth opportunities to both technical and non-technical audiences
Act as the voice of the customer internally, collaborating with Delivery, Product, and Engineering to resolve issues and improve processes
Develop a strong understanding of customer workflows and data consumption patterns to proactively identify opportunities for increased adoption and expanded use cases