Engagement Manager - Data as a Service
snorkelai • New York City, NY (Hybrid); Redwood City, CA (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
Posted: May 1, 2026
Job Description
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.
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
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
Bonus points for:
- Experience working with AI/ML workflows, data annotation, or data infrastructure
- Experience driving net revenue retention (NRR) or expansion metrics in enterprise accounts
All offers include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Additional Content
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.
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
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
Bonus points for:
- Experience working with AI/ML workflows, data annotation, or data infrastructure
- Experience driving net revenue retention (NRR) or expansion metrics in enterprise accounts
All offers include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.