Senior Product Manager – Agents and Intelligence
New
J
JobgetherContract lifecycle management
Full-time remote position within the United States.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 5 years of product management experience within a fast-paced software company.
- Required Skills
- Product ManagementGenerative AI
Requirements
- At least 5 years of product management experience within a fast-paced software company.
- Advanced knowledge of current approaches to building, measuring, and improving generative AI applications for B2B environments.
- Experience defining success metrics, evaluating product performance, and using data to guide product decisions.
- Background in enterprise B2B software; legal technology, contract lifecycle management, ERP, CRM, or BPM experience is preferred.
- Experience collaborating with engineering teams to design, improve, or evolve APIs for integrations, extensibility, and AI agent capabilities.
- Ability to prioritize effectively and connect day-to-day execution with broader business strategy.
- Experience with agent frameworks, multi-agent collaboration, or orchestration platforms is preferred.
- Familiarity with Model Context Protocol (MCP), agent tools, or comparable technologies is an advantage.
- Experience building and scaling generative AI or agent-based products for enterprise customers is preferred.
- Experience with enterprise no-code platforms and extensibility strategies is beneficial.
- Willingness to travel up to 10% for customer workshops, conferences, and research activities.
Responsibilities
- Own the roadmap and execution of agent-driven solutions, aligning product investments with business objectives and measurable customer and commercial impact.
- Co-lead initiatives that introduce AI-powered insights and optimizations across the product.
- Identify contract lifecycle use cases where intelligent agents can automate tasks, support decisions, and improve operational outcomes.
- Define, monitor, and optimize KPIs for agentic workflows, including adoption, customer satisfaction, and return on investment.
- Partner with engineering to evolve APIs and improve data accessibility for agent-driven solutions.
- Collaborate with UX and design teams to understand user needs and create user-centered AI experiences.
- Prioritize the product backlog and develop user stories, acceptance criteria, and product specifications.
- Track developments in contract lifecycle management, generative AI, agent frameworks, and competing products to inform strategy.
- Partner with product marketing, sales enablement, customer success, and other stakeholders on launches, adoption, and market positioning.
- Communicate the value and capabilities of intelligent agent solutions to internal stakeholders, customers, and external audiences.
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