AI Product Manager I (US)

Manufacturing & Technology: Email-based order processing automation, predictive asset maintenance workflows, or software development lifecycle (SDLC) speed-ups.

Google Cloud Architecture Alignment: Consult clients on utilizing the Gemini Enterprise Agent Platform to replace traditional, rigid chatbots with dynamic, multi-agent frameworks.

Agile Discovery: Facilitate workshops with business and IT stakeholders to evaluate business processes, estimate ROI, and map out the vision for an "agentic taskforce."

Product Development and Execution (Product Management)

You will own the lifecycle of the AI agent from conceptualization to stable production deployment, managing cross-functional technical teams.

Roadmap & Backlog Management: Qualify agent use cases based on technical feasibility and business impact. Maintain the product backlog using Agile methodologies.

Technical & Functional Specifications: Translate complex business rules into concrete logic definitions. You will write specifications outlining:

Agent Logic and Reasoning: Defining paths using Agent Studio (for low-code/no-code workflows) or specifying requirements for the Agent Development Kit (ADK) (for developer code-first graph-based sub-agent networks).

Data Grounding: Defining how agents safely connect to enterprise data sources (e.g., BigQuery, Google Workspace, or third-party CRM/ERP systems) using secure connectors.

Integrations: Utilizing the Agent2Agent (A2A) protocol to ensure a Google agent can seamlessly hand off tasks to partner agents (e.g., Salesforce, Workday, ServiceNow).