AI Product Manager

Role Summary:

The AI Product Manager – VoiceBOTs plays an organization-wide leadership role in the strategic development, deployment, and ownership of conversational AI solutions, specifically voice bots, across the organization. This position oversees voicebot initiatives that span multiple departments, including CRM for Telesales, Collections, and Operations Customer Service, ensuring that solutions are tailored to varied business needs throughout the company. The ideal candidate guides the full lifecycle of voicebot products—primarily focusing on Google Dialogflow and integration with Genesys Engage (on-premise)—and excels at uniting product vision, technical expertise, and stakeholder management. The goal is to deliver scalable, customer-centric voicebot experiences for diverse operational contexts across the organization.

Responsibilities:

• Product Strategy & Roadmap
  • Define and own the product vision and roadmap for voicebot solutions using Google Dialogflow.
  • Align voicebot capabilities with business goals, customer experience standards, and operational efficiency targets.
  • Evaluate and prioritize features based on impact, feasibility, and user feedback.
    
    
• VoiceBOT Ownership & Delivery
  • Lead end-to-end delivery of voicebot products, from ideation to deployment and optimization.
  • Ensure seamless integration with Genesys Engage telephony systems and other backend platforms.
  • Collaborate with vendors, IT, and business teams to manage configurations, call flows, and persona design.
    
    
• Technical Oversight
  • Provide hands-on guidance on Dialogflow CX/NLU configurations, intents, entities, and fulfillment logic.
  • Oversee testing, QA, and performance tuning of voicebots across multiple use cases (collections, onboarding, telesales).
  • Monitor and improve voicebot KPIs such as call containment rate, sentiment accuracy, and escalation triggers.
    
    
• Stakeholder Engagement
  • Work closely with operations, collections, CRM, and customer experience teams to gather requirements and feedback.
  • Coordinate with external partners (e.g., Google, Genesys, vendors) for solution alignment and support.
    
    
• Team Leadership & Collaboration
  • Manage a cross-functional team of AI specialists, data scientists, and QA engineers.
  • Foster a culture of innovation, experimentation, and continuous improvement.
    
    

Qualifications:

• Master's degree in Economics, Finance, Statistics, Mathematics, Computer Science, Physics, Engineering or any related course
• Has at least 2 years of work experience related to AI field
• Technical Skills:
  • Basic knowledge of machine learning, deep learning, and NLP methodologies.
  • Solid understanding of AI/ML concepts, including data processing, model development, and deployment (MLOps).
  • Familiarity with cloud platforms (Azure, AWS, or GCP) and data architectures.
  • Preferred:
    • Fundamental-level Microsoft Azure certifications such as Azure Fundamentals (AZ-900), Azure AI Fundamentals (AI-900), or Azure Data Fundamentals (DP-900).
    • Demonstrated ability to define project scope, objectives, and success metrics.
    • Data-driven decision-making mindset with a solid grasp of business goals and strategies.
    • Proven track record of leading and managing teams.
    • Ability to influence decision-making processes and negotiate priorities across the organization.
      
      
      
  • Nice to have:

    • Experience with AI applications within finance industry or domain.

    • Practical know-how with modern data processing frameworks (e.g., Spark, Kafka) for real-time data pipelines.

    • Exposure to database systems (SQL & NoSQL), data lakes, and data warehouse solutions.

    • Experience developing training materials for non-technical stakeholders to drive AI adoption.

    • Relevant Microsoft certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, or Azure Solutions Architect Expert.