AI Product Manager I

HCLTech is a company focused on leveraging advanced technology for business solutions, and they are seeking an AI Product Manager I. This role involves bridging business strategy and technical implementation to design, build, and deploy autonomous AI agents that automate complex workflows across various industries.

Responsibilities:

• You will drive the adoption of Agentic AI by demonstrating how autonomous agents can shift an organization from reactive software usage to proactive, automated process execution
• Apply deep industry knowledge to pinpoint high-value automation use cases: Financial Services (FS): Automating credit risk reporting, compliance checks, or fraud investigation workflows. Retail & Consumer Packaged Goods (RCPG): Real-time supply chain adjustments, automated inventory routing, or predictive marketing campaign launches. Life Sciences & Healthcare (LSH): Accelerating clinical trial documentation search, patient intake routing, or medical literature synthesis. Manufacturing & Technology: Email-based order processing automation, predictive asset maintenance workflows, or software development lifecycle (SDLC) speed-ups
• Consult clients on utilizing the Gemini Enterprise Agent Platform to replace traditional, rigid chatbots with dynamic, multi-agent frameworks
• Facilitate workshops with business and IT stakeholders to evaluate business processes, estimate ROI, and map out the vision for an 'agentic taskforce.'
• You will own the lifecycle of the AI agent from conceptualization to stable production deployment, managing cross-functional technical teams
• Qualify agent use cases based on technical feasibility and business impact. Maintain the product backlog using Agile methodologies
• 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)
• Defining how agents safely connect to enterprise data sources (e.g., BigQuery, Google Workspace, or third-party CRM/ERP systems) using secure connectors
• Utilizing the Agent2Agent (A2A) protocol to ensure a Google agent can seamlessly hand off tasks to partner agents (e.g., Salesforce, Workday, ServiceNow)
• Define functional requirements for safety and performance. Work with engineers to utilize Agent Simulation and Agent Evaluation tools to test agents against synthetic user profiles and prevent prompt injection vulnerabilities via Model Armor
• An agent is only valuable if it is trusted and adopted. You will act as the ultimate product evangelist and governance lead
• Serve as the central hub connecting Engineering, User Experience (UX), Sales, and Marketing teams to ensure a smooth product rollout
• Collaborate with enterprise IT admins to ensure agents are securely deployed into the organization's Gemini Enterprise app hub. Ensure every custom agent is registered under an Agent Identity and governed via the central Agent Registry
• Gather direct user feedback from client teams, analyze Agent Observability traces to see how the agent reasons through its tasks, and continuously refine prompts, tools, and workflows to improve completion rates
• Monitor and present product performance metrics, such as: Task Success Rate (percentage of workflows completed without human intervention). Time-to-Resolution Reduction (e.g., reducing email processing times from hours to real-time). API & Compute Cost Efficiency (tracking vCPU and token spend)

Requirements:

• Experience in AI product management or related field
• Strong understanding of Google Cloud's Gemini Enterprise Agent Platform
• Ability to bridge business strategy and technical implementation
• Experience in designing, building, and deploying autonomous AI agents
• Knowledge of industry-specific automation use cases in Financial Services, Retail & Consumer Packaged Goods, Life Sciences & Healthcare, and Manufacturing & Technology
• Experience with Agile methodologies and product backlog management
• Ability to translate complex business rules into technical specifications
• Experience with data grounding and secure data connections
• Knowledge of integrations using Agent2Agent (A2A) protocol
• Experience in defining functional requirements for safety and performance
• Ability to work with engineers on testing agents against synthetic user profiles
• Experience in cross-functional orchestration among Engineering, UX, Sales, and Marketing teams
• Knowledge of deployment and enterprise governance for AI agents
• Ability to gather user feedback and analyze agent performance metrics