Role Overview
We are seeking a strategic and results-driven AI Product Manager - VoiceBOTs to lead the strategic development, deployment, and ownership of conversational AI voicebot solutions across multiple departments, including CRM Telesales, Collections, and Customer Service. In this role, you will guide the full lifecycle of voicebot products—focusing primarily on Google Dialogflow and integration with Genesys Engage telephony systems—to deliver scalable, customer-centric experiences.
Key Responsibilities
- Product Strategy & Roadmap:Define and own the product vision and roadmap using Google Dialogflow, aligning voicebot capabilities with business goals, customer experience standards, and operational efficiency targets.
- End-to-End Delivery:Lead the deployment and optimization of voicebot products while ensuring seamless integration with telephony systems and backend platforms.
- Technical Oversight:Provide hands-on guidance on Dialogflow CX/NLU configurations, intents, entities, and fulfillment logic.
- Performance Tuning:Oversee testing, QA, and performance optimization across multiple use cases while monitoring key KPIs like call containment rates, sentiment accuracy, and escalation triggers.
- Stakeholder & Team Leadership:Manage a cross-functional team of AI specialists, data scientists, and QA engineers while collaborating closely with business units and external partners (e.g., Google, Genesys).
Position RequirementsEducation & Experience
- Education:Master's degree in Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, Physics, or a related course.
- Experience:At least 2 years of work experience directly related to the AI field.
- Leadership:A proven track record of leading and managing cross-functional teams.
Technical & Soft Skills
- Solid understanding of AI/ML concepts, MLOps, deep learning, data processing, and NLP methodologies.
- Familiarity with cloud platforms (GCP, AWS, or Azure), with preferred fundamental certifications like AZ-900, AI-900, or DP-900.
- Data-driven decision-making mindset with strong problem-solving skills and an awareness of AI ethics and bias reduction.
- Excellent communication and storytelling skills with full fluency in written and spoken English.
Nice-to-Have Qualifications
- Experience developing AI applications within the finance industry or domain.
- Practical know-how with modern data processing frameworks (e.g., Spark, Kafka) for real-time data pipelines and exposure to database systems (SQL/NoSQL) or data lakes.
- Advanced certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, or Azure Solutions Architect Expert.
