The Senior Product Manager - Business Applications AI will join the team to own and prioritize an AI-powered roadmap for enterprise business applications. The role involves identifying manual bottlenecks and applying AI and agentic workflows to streamline critical journeys like Quote-to-Cash, license provisioning, and financial reconciliation. You will build and iterate on functional prototypes using AI-native tools such as Cursor and Lovable to validate requirements before engineering handoff. Key responsibilities include defining accuracy guardrails, curating Golden Sets from internal telemetry, and managing LLM mechanics like RAG architectures. Required expertise includes Salesforce CRM, SAP, Workday, Snowflake, or Databricks. You must demonstrate technical literacy in vibe-coding and experience with enterprise domains like Sales Ops, Finance, Customer Success, or Business Intelligence to solve complex operational problems.
What does a Product Manager earn in California?
Median $222500 from 327 postings across 57 companies.
Own and prioritize an AI-powered roadmap for business applications across Sales, Finance, Support, and Customer Success.
Identify manual bottlenecks and apply AI/Agentic workflows to streamline critical enterprise journeys like Quote-to-Cash.
Build and iterate on functional prototypes using AI-native tools to validate requirements before handing off to Engineering.
Define error budgets, accuracy guardrails, and compliance standards for AI outputs within business-critical systems.
Create and version-control "Golden Sets" of enterprise data to grade AI model performance in real-world scenarios.
Ensure data privacy, financial integrity, and system governance for all AI-driven business processes.
What we're looking for
Must have 8 years of experience with a Bachelor’s degree, 6 years with a Master’s, or a PhD with 3 years of experience in Product Management.
Must have experience in Product Management for Enterprise Applications, Business Systems, or Data/BI Architecture.
Must have a proven track record of delivering features in domains like Sales/Revenue Ops, Licensing, Finance/ERP, Customer Support, Customer Success, or BI/Data.
Must have hands-on experience using GenAI tools to turn prompts into functional prototypes to validate requirements for Engineering.
Must have a deep understanding of LLM mechanics, including context windows, hallucinations, RAG architectures, and Agentic workflows for enterprise processes.
Experience with Salesforce AI, Workday Extend, SAP BTP, Gainsight, or cloud data stacks like Snowflake and Databricks (preferred).
Track record of driving large-scale digital transformations across Lead-to-Cash, Hire-to-Retire, or Telemetry-to-Insight lifecycles (preferred).
Portfolio or background demonstrating the use of AI to orchestrate business solutions, automate workflows, or generate business intelligence (preferred).