Lead Application Product Manager - Customer Success

DocuSign DocuSign · Enterprise · San Francisco, CA · IT Infrastructure & Operations

Lead Product Manager for internal applications at DocuSign, focusing on customer success and operations. The role involves defining product vision and roadmaps, partnering with stakeholders and engineering, and driving buy vs. build decisions. Key responsibilities include mapping user journeys, defining data strategies, and shipping AI/ML-powered capabilities like chatbots or recommendations. Experience with AI/ML products, B2B SaaS, and CRM/CS ecosystems is required.

What you'd actually do

  1. Define a multi-year product and technology roadmap for your application domain, aligned to company growth goals (e.g., retention, NRR, CSAT, operational efficiency) and IAM strategy
  2. Act as a strategic partner to business stakeholders (e.g., Customer Success, Operations), translating their objectives (such as reducing time-to-resolution or improving digital self-service) into clear product requirements and system capabilities
  3. Drive structured "buy vs. build" decisions for internal tools and platforms, evaluating market solutions versus custom development and shaping vendor integration strategies where appropriate
  4. Map end-to-end user journeys to identify bottlenecks and "swivel-chair" workflows, and design experiences that simplify work for internal users while improving customer outcomes
  5. Lead the strategy for unified data and a 360-degree view of key entities (e.g., customers, accounts, products), ensuring data flows reliably across CRM, billing, product usage, and support systems

Skills

Required

  • Product management
  • AI/ML products
  • B2B SaaS platforms
  • CRM/CS ecosystems
  • APIs
  • data pipelines/warehousing
  • identity/entitlements
  • shipping AI/ML capabilities
  • influencing without authority
  • product briefs
  • PRDs
  • status updates

Nice to have

  • Deep empathy for internal users
  • shadowing workflows
  • eliminating friction

What the JD emphasized

  • meaningful work on AI/ML products
  • Experience shipping AI- or ML-powered capabilities
  • using data to monitor and improve them over time
  • AI-powered and data-driven features
  • applying LLMs, agentic workflows, or advanced analytics

Other signals

  • shipping AI/ML products
  • internal applications
  • customer success
  • product roadmap