Sr. Product Manager

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity.

Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e‑signature and contract lifecycle management (CLM).

We are seeking an experienced, visionary Sr. Product Manager to lead the development of AI‑powered data solutions that drive field seller productivity. In this role, you will define and execute the product strategy for reporting, analytics, and agentic solutions that empower our sales teams. You will collaborate closely with Sales stakeholders, engineering, data science, and customer success teams to deliver impactful data products that streamline sales operations and maximize seller effectiveness.

Your work will be instrumental in enabling Docusign’s growth by providing actionable insights and automation to our field seller community.

This position is an individual contributor role reporting to the Sr. Manager, Global Data & Analytics.

• Develop and execute the product roadmap for AI‑powered reporting, analytics, and agentic solutions that enhance field seller productivity
• Own the strategy and delivery of intelligent enterprise data solutions that streamline sales operations using AI‑first principles
• Partner closely with the field seller community to deeply understand the sales cycle and identify productivity opportunities through data and AI
• Collaborate with Sales and Customer Success teams to gather business requirements and translate them into impactful data reporting solutions
• Coordinate with data engineering and data science teams to launch and enhance data reporting solutions
• Communicate product updates, roadmaps, and impact analyses to leadership and key stakeholders
• Leverage data and advanced analytics tools to drive business decisions and measure the impact of new features on sales productivity

Hybrid:
Employee divides their time between in‑office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in‑office expectation)

Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position’s job designation depending on business needs and as permitted by local law.

• Bachelor’s degree in Business, Information Systems, Computer Science, or a related field
• 8+ years of experience in Product Management or 6+ years with Masters Degree
• Experience with SQL for data querying, analysis, and validation, demonstrating a strong data product management foundation
• Proven track record of driving innovation, vision, and creative problem solving leveraging product management mindset
• Experience building, deploying or experimenting with Large Language Models (LLMs) and Generative AI (GenAI) applications
• Ability to define a clear product vision, create a product roadmap, and prioritize features based on measurable business value
• Experience managing product backlogs, writing detailed user stories, and leveraging JIRA for tracking

• Exceptional communication skills to act as the bridge between highly technical Data Science teams, Sales Executives, and Data Engineering teams
• Excellent communication, stakeholder management, and problem‑solving abilities
• Experience supporting sales field teams and a deep understanding of the sales lifecycle
• Experience with Salesforce, Tableau, JIRA, and Snowflake
• Sufficient technical knowledge to debate solutions and trade‑offs with engineers and data scientists, focusing on the what and why rather…