AI Product Manager

Gainsight is building an AI-powered retention engine and CustomerOS platform for customer success. The AI Product Manager will lead end-to-end Atlas deployments for strategic customers, including technical implementation, ROI modeling, renewals, and customer outcome management. The role will also translate field learnings into product and engineering priorities while collaborating cross-functionally with internal and customer teams.

Responsibilities:

• Deploy Atlas in customer environments
• Own the customer engagement from discovery through full scope delivery
• Define and document implementation requirements for each account, validated against the customer's real data and workflows
• Own resolution of blockers across support, engineering, and the customer's IT
• Lead the technical implementation of Atlas agents inside customer tenants: data mapping across objects, fields, and tokens, connector configuration, and authentication setup spanning DNS, SSO, and Salesforce integrations
• Support the rollout of AI agents alongside an AI native services team leveraging both agentic and human engagement
• Own roadmap prioritization of each deployment and reconcile it against broader customer and engineering requirements
• Construct ROI models and value narratives tailored to each account, and present them with credibility to customer leadership
• Run go or no-go reviews on new opportunities, weighing business cases against effort and upside, and make a clear recommendation
• Partner on services scoping and pricing for new deployments
• Lead renewal reviews, implementation, and outcome-based conversations
• Define and design agentic renewal workflows to drive specific customer goals and ensure the renewals team is trained to successfully execute the process
• Surface problems, own the path forward, and clarify ownership
• Carry the reality of the field back to the core team: the gaps, the friction, the recurring failure modes, and the requests that recur across accounts
• Prioritize product fixes so that hard-won lessons compound
• Contribute to internal reviews and shape the roadmap with real evidence
• Document what you learn, configurations, failure modes, ROI frameworks, in forms the next deployment can actually use, not just the one you're in

Requirements:

• 3-5 years of product management experience with technically complex, integration-heavy software
• Exceptional relationship and communication skills. You build trust quickly with senior stakeholders, navigate organizational dynamics with ease, and stay composed and clear when conversations get difficult
• Experience with AI native services, distributed systems, databases, training ML models, RAG, and LLMs
• Hands-on technical fluency: data modeling, APIs and connectors, authentication and DNS fundamentals, and enough comfort with SQL or spreadsheets to build and defend an ROI model yourself
• Sound judgment under ambiguity. You can run a room with senior people, make a recommendation without complete information, and own the result
• Comfort owning outcomes across teams you do not manage, including support, engineering, services, and the customer's own organization
• A bias to action and a willingness to be the first person to make something work before it is fully productized
• Background in customer success, RevOps, data, or AI and ML products