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). What you'll do As a P4 AI Product Manager Analyst for Martech, you own Agent Use Case Definition & Business Outcomes by identifying high-impact business workflows. You define technically viable agent requirements and translate business problems into clearly defined agent capabilities feasible within the enterprise tech stack. For Applications Workflow Design & Orchestration, you define the end-to-end workflow an agent will perform across enterprise systems, specifying triggers, context, actions, and escalation paths. You handle Collaboration, Value measurement, and Continuous improvement by defining success metrics, tracking outcomes, and refining agent behaviors based on operational feedback. Finally, you manage Autonomous Boundaries and Safety by determining the extent of agent autonomy, defining guardrails, approval checkpoints, and the human-in-the-loop model. This position is an individual contributor role reporting to the Director, Martech & Prospecting Applications. Responsibility Identify the highest-value problems for business development, sales and account executives where an agent can save time, reduce effort, and take useful action Be very savvy with data, crunch the current state funnel metrics, and pipeline performances to determine the highest value use cases to agentify Influence senior leaders and cross-functional teams on use cases we should automate, what to build first, and how to stay at the forefront of this space Understand intent signals, prospecting signals, propensity scores, next best recommendations etc to determine the best execution strategies for prospecting Rapidly evaluate new capabilities from model providers, tooling ecosystems, and internal platforms, and translate them into clear product bets Build scrappy but convincing prototypes using available models, agent frameworks, tools, and lightweight interfaces to test usefulness, trust, and feasibility Partner with engineering, ML, design, and platform teams to turn promising prototypes into scalable product experiences Shape how memory, context, orchestration, permissions, and human handoff should work in prospecting journeys Define safe patterns for agents that take action, including clear explanations, user approvals, visibility into what the agent is doing, and recovery paths when things go wrong Establish success metrics, launch criteria, and learning loops for these experiences, balancing ambition with trust, reliability, latency, and cost Job Designation 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. What you bring Basic 6+ years of product management experience, including meaningful work on AI/ML products, automation systems, developer tools, platforms, or other technically sophisticated products. Hands-on builder mindset, with the ability to use model APIs, 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 to strategy, prototype, launch, and measurable impact Preferred 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 Strong point of view on when an agent should act autonomously, when it should ask for permission, and how to keep users in controlStrong technical fluency and comfort working at the boundary of product and engineering and be able to reason about APIs, orchestration, data flows, permissions, latency, and failure modes Strong judgment in trust-sensitive experiences, including transparency, control, privacy, and reliability Excellent written and verbal communication skills, with the ability to create clarity and alignment across senior cross-functional stakeholders Strong Data Analysis, Data Science and engineering skills Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice #LI-Hybrid #LI-SA4
Senior Product Manager, AI
DocuSign · Enterprise · Bangalore, India · IT Infrastructure & Operations
Product Manager for AI Agents in Martech, focusing on defining agent use cases, requirements, workflows, and safety guardrails for enterprise applications. Involves prototyping, collaboration with engineering/ML, and defining success metrics.
What you'd actually do
- Own Agent Use Case Definition & Business Outcomes by identifying high-impact business workflows.
- Define technically viable agent requirements and translate business problems into clearly defined agent capabilities feasible within the enterprise tech stack.
- Define the end-to-end workflow an agent will perform across enterprise systems, specifying triggers, context, actions, and escalation paths.
- Manage Autonomous Boundaries and Safety by determining the extent of agent autonomy, defining guardrails, approval checkpoints, and the human-in-the-loop model.
- 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
- AI/ML products
- automation systems
- developer tools
- platforms
- technically sophisticated products
- Hands-on builder mindset
- ability to use model APIs
- agent tooling
- simple code in Python or TypeScript/JavaScript to create or guide working prototypes
- taking new product areas from ambiguous opportunity to strategy, prototype, launch, and measurable impact
- Strong technical fluency
- comfort working at the boundary of product and engineering
- reason about APIs, orchestration, data flows, permissions, latency, and failure modes
- Strong judgment in trust-sensitive experiences, including transparency, control, privacy, and reliability
- Excellent written and verbal communication skills
- ability to create clarity and alignment across senior cross-functional stakeholders
- Strong Data Analysis
- Data Science
- engineering skills
Nice to have
- building assistants
- agents
- copilots
- AI products that use tools to complete tasks
- Familiarity with memory
- tool calling
- browser or computer use
- voice
- multimodal interaction
- agent orchestration
- Background in software engineering
- ML
- data science
- similarly technical field
- Strong point of view on when an agent should act autonomously
- when it should ask for permission
- how to keep users in control
What the JD emphasized
- AI/ML products
- agent
- agents
- agent
- agent
- agent
- agent
- agent
- agent
- agent
- agent
- agent
Other signals
- Define technically viable agent requirements
- translate business problems into clearly defined agent capabilities
- define the end-to-end workflow an agent will perform
- determining the extent of agent autonomy, defining guardrails, approval checkpoints, and the human-in-the-loop model
- build scrappy but convincing prototypes using available models, agent frameworks, tools
- Shape how memory, context, orchestration, permissions, and human handoff should work