Duties:
- Manage ideation, business cases, demand and roadmaps across cross functional internal teams to develop and steer product roadmap
- Work with business teams to identify the key processes that can be automated using the latest tools & technology (AI, Agentic, Workflow automations) for efficiency gains
- Own product development of complex workflows from conception to launch focused on enterprise integrations, process automation and data flows
- Document functional and non-functional requirements, ensuring Engineering teams have 4-6 weeks worth of refined backlog
- Deliver quarterly objectives and work within and plan against a defined project/product release schedule
- Recommend new methods for efficiency or business process engineering/optimization to support our key business partners
- Conduct Demos to business units of integrations and automation projects
- Run User Acceptance Testing and Sign-off on behalf of the business, as needed
- Plan and coordinate across multiple product & engineering teams
- Bachelor’s degree in Computer Science, Engineering, Business, or a related field; Master’s degree preferred.
- 4+ years experience, preferably as a Product Manager at a SaaS company, for an internal product, enterprise/ integrations/API development or enterprise data management with prior experience in Engineering roles.
- Hands-on experience in AI automations, API Integrations, Business & Robotics process automation and their patterns, protocols, and tools.
- Functional understanding of Enterprise apps used across CX/HR/Finance/IT domains (SFDC, Workday, Netsuite, Gsuite, Slack, etc.) and their integrations via Mulesoft/Airflow/Workato or similar tools.
- Knowledge of Cloud infrastructure (AWS/GCP) and Cloud services.
- Hands-on experience in writing PRD, defining personas and user stories.
- Experience with defining non-functional requirements (Automation, CI/CD, Security, load/performance testing)
- Experience with vendor management and third party software implementations
- Experience with reporting and analyzing key metrics and incorporating them into decision- making processes
- Bachelor’s degree in Computer Science, Engineering, Business, or a related field; Master’s degree preferred.