Product Manager (Gen AI)

We are seeking an experienced Product Manager to lead the development and implementation of a comprehensive AI platform featuring third-party LLM integration, enterprise data source connectivity, and agentic orchestration capabilities. This role will be critical in defining product strategy, managing the product roadmap, and ensuring successful delivery of this advanced AI platform that meets stakeholder needs and drives business value.

Key Responsibilities

Product Strategy & Vision

• Define and communicate product vision for the AI platform aligned with the client's strategic objectives
• Develop and maintain product roadmap for the three core components:
• Third-Party LLM Integration Framework (e.g. OpenAI, Gemini, WOG Maestro)
• Enterprise Data Source Integration with RAG pipeline (e.g. Sharepoint, Teams, JIRA, Confluence)
• Agent Orchestration System with autonomous task completion
• Conduct market research and competitive analysis to identify opportunities and differentiation strategies
• Define success metrics and KPIs for platform adoption and performance

Product Planning & Prioritisation

• Lead product discovery workshops with stakeholders to identify user needs and business objectives
• Prioritise features and capabilities based on business value, technical feasibility, and user impact
• Create and maintain product backlog with clear user stories and acceptance criteria
• Define functional requirements for enterprise data source integrations based on identified use cases
• Specify requirements for agentic bots aligned with business scenarios and user workflows

Enterprise Data Integration Strategy

• Define product requirements for secure enterprise system connectors
• Establish product specifications for Backend ELT Pipeline processes and user-friendly frontend interfaces
• Oversee secure data transfer workflows and data security implementation strategy
• Define RAG pipeline capabilities including query processing, retrieval mechanisms, and response generation
• Prioritise document processing features for various formats and vector embedding requirements

Agent Orchestration & Automation Product Development

• Define product features for backend infrastructure supporting agent management
• Establish workflow orchestration capabilities and tool integration priorities
• Specify multi-step workflow automation features and autonomous task completion functionality
• Collaborate with stakeholders to identify and prioritise connected data source integrations
• Define performance metrics and monitoring dashboards for agent systems

Administrative & Monitoring Features

• Define user management features including CRUD operations, role assignment, and access control
• Specify bot configuration interface capabilities and deployment controls
• Establish data source management features including connection configuration and status monitoring
• Design dashboard requirements for bot usage tracking, conversation metrics, and user engagement
• Define custom metric capabilities and reporting features

Quality Assurance & Testing Strategy

• Define acceptance criteria and test scenarios for bot functionality using Litmus or Moonshot frameworks
• Establish evaluation frameworks including LLM-as-a-Judge systems
• Specify performance testing requirements including load testing and stress testing parameters
• Oversee UAT planning and remediation support for performance testing phases
• Define security testing requirements including VAPT and vulnerability assessment needs

Stakeholder Management & Communication

• Serve as primary liaison between the client’s stakeholders, technical teams, and AWS Professional Services
• Lead sprint planning, backlog refinement, and milestone tracking activities
• Conduct bi-weekly status reporting and stakeholder alignment meetings
• Manage expectations regarding deliverables, timelines, and technical constraints
• Facilitate go-to-market planning and user adoption strategies
• Lead knowledge transfer and training sessions for up to 5 participants per session

Requirements

Educational Background

• Bachelor's degree in Business Administration, Information Systems, Computer Science, or related field
• MBA or Master's degree in related field preferred
• Professional certifications in product management (CSPO, CPM) or AI/ML technologies are advantageous

Professional Experience

• 5+ years of experience in product management for complex technology products
• Minimum 2 years of experience with AI/ML or LLM-based product development
• Proven track record of successfully launching and scaling enterprise software products
• Experience working with AWS cloud services and enterprise system integrations
• Experience with government or public sector digital transformation projects preferred

AI & Technical Expertise

• Strong understanding of Large Language Models (LLMs) and their business applications
• Knowledge of RAG (Retrieval-Augmented Generation) architectures and vector databases
• Familiarity with AI governance frameworks and ethical AI considerations
• Understanding of enterprise data integration patterns and API management
• Experience with cloud platforms (AWS preferred) and containerisation technologies
• Knowledge of AI safety testing frameworks and guardrail implementations

Platform Specific Skills

• Experience with multi-modal AI systems and agent orchestration concepts
• Understanding of prompt engineering and chain-of-thought implementations
• Knowledge of AI model evaluation metrics and performance optimisation
• Familiarity with enterprise security requirements and compliance frameworks
• Experience with agile methodologies and product development lifecycle

Core Competencies

• Excellent stakeholder management and executive communication skills
• Strong strategic thinking and data-driven decision-making abilities
• Ability to translate technical AI concepts for non-technical stakeholders and vice versa
• Customer-centric mindset with focus on user experience and value delivery
• Experience with product management tools (JIRA, Confluence, Aha!, ProductBoard)
• Understanding of government security clearance processes and information handling protocols
• Proven ability to influence without authority and drive cross-functional alignment

Desirable Experience

• Knowledge of Singapore government digital services and WOG systems
• Familiarity with AI testing frameworks (Litmus, Moonshot, Sentinel)
• Experience with vector databases and embedding technologies
• Understanding of enterprise data governance and privacy regulations
• Experience launching AI products in regulated environments
• Track record of driving product adoption and measuring product-market fit