Product Manager, AI

DocuSign DocuSign · Enterprise · Bangalore, India · IT Infrastructure & Operations

Product Manager for AI focusing on agent use case definition, business outcomes, and workflow design for prospecting within the enterprise tech stack. Responsibilities include defining agent capabilities, orchestrating workflows across enterprise systems, measuring value, managing autonomy, and defining guardrails and human-in-the-loop models. Requires experience with AI/ML products, automation systems, and building prototypes.

What you'd actually do

  1. own Agent Use Case Definition & Business Outcomes by identifying high-impact business workflows
  2. define the end-to-end workflow an agent will perform across enterprise systems, specifying triggers, context, actions, and escalation paths
  3. determine the extent of agent autonomy, defining guardrails, approval checkpoints, and the human-in-the-loop model
  4. Identify the highest-value problems for business development, sales and account executives where an agent can save time, reduce effort, and take useful action
  5. Build scrappy but convincing prototypes using available models, agent frameworks, tools, and lightweight interfaces to test usefulness, trust, and feasibility

Skills

Required

  • Product Management experience (10+ years)
  • Experience with AI/ML products, automation systems, developer tools, or platforms
  • Hands-on builder mindset
  • Ability to use model APIs, agent tooling, and simple code (Python or TypeScript/JavaScript) for prototypes
  • Proven track record of taking new product areas from opportunity to launch and impact
  • Strong technical fluency
  • Strong judgment in trust-sensitive experiences (transparency, control, privacy, reliability)
  • Excellent written and verbal communication skills
  • Strong Data Analysis, Data Science and engineering skills

Nice to have

  • Experience building assistants, agents, copilots, or AI products that use tools to complete tasks
  • Familiarity with memory, tool calling, browser or computer use, voice, multimodal interaction, or agent orchestration
  • Background in software engineering, ML, data science, or a similarly technical field

What the JD emphasized

  • AI/ML products
  • automation systems
  • agent frameworks
  • agent tooling
  • agent autonomy
  • agent behaviors

Other signals

  • agent use case definition
  • agent requirements
  • workflow design and orchestration
  • autonomous boundaries and safety
  • human-in-the-loop model