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Docusign

Runs electronic signing and agreement workflows

Lead Product Manager - AI, Martech

Product ManagementUpdated on Nov 10
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 6 years of product management experience, including meaningful work on AI/ML products, automation systems, developer tools, platforms, or other technically sophisticated products.
  • Ability to use model application programming interfaces, agent tooling, and simple code in Python or TypeScript/JavaScript to create or guide working prototypes.
  • Proven track record of taking new product areas from ambiguous opportunity through strategy, prototype, launch, and measurable impact.

Responsibilities

  • Identify high-value problems for business development, sales, and account executives where an agent can save time, reduce effort, and take useful action.
  • Analyze current-state funnel metrics and pipeline performance to determine high-value use cases for agent automation.
  • Influence senior leaders and cross-functional teams on which use cases to automate, what to build first, and how to remain at the forefront of the space.
  • Understand intent signals, prospecting signals, propensity scores, and next-best recommendations to determine prospecting execution strategies.
  • Rapidly evaluate new capabilities from model providers, tooling ecosystems, and internal platforms, and translate them into product bets.
  • Build prototypes using available models, agent frameworks, tools, and lightweight interfaces to test usefulness, trust, and feasibility.
  • Partner with engineering, machine learning, design, and platform teams to turn promising prototypes into scalable product experiences.
  • Shape how memory, context, orchestration, permissions, and human handoff work in prospecting journeys.
  • Define safe patterns for agents that take action, including explanations, user approvals, visibility into agent activity, and recovery paths for failures.
  • Establish success metrics, launch criteria, and learning loops for these experiences, balancing ambition with trust, reliability, latency, and cost.
  • Identify agent use cases and business outcomes by defining technically viable agent requirements and capabilities that fit the enterprise technology stack.
  • Define end-to-end agent workflows across enterprise systems, including triggers, context, actions, and escalation paths.
  • Define success metrics, track outcomes, and refine agent behaviors based on operational feedback.
  • Determine agent autonomy boundaries and define guardrails, approval checkpoints, and human-in-the-loop models.

Desired Qualifications

  • 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, machine learning, data science, or a similarly technical field.
  • Strong point of view on when an agent should act autonomously, when it should ask permission, and how to keep users in control.
  • Strong technical fluency at the boundary of product and engineering, including reasoning about application programming interfaces, orchestration, data flows, permissions, latency, and failure modes.
  • Strong judgment in trust-sensitive experiences, including transparency, control, privacy, and reliability.
  • Strong data analysis, data science, and engineering skills.

About the Company

Docusign

Runs electronic signing and agreement workflows

Docusign runs electronic signing and agreement management software for businesses, letting people approve contracts online and track the steps around each agreement. Its eSignature product routes documents to signers and records who signed, while contract lifecycle tools organize preparation, negotiation, and approvals. The Intelligent Agreement Management platform stores contracts in a searchable repository and uses AI to extract terms and connect agreement data to business workflows. Customers use its web applications or embed signing through APIs, and pay for subscriptions based on users, features, and document allowances. Docusign was founded in 2003 and is headquartered in San Francisco.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2003

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