AI Product Manager

AI Product Manager – Conversational AI (Voice & NLU)

The ideal candidate blends technical NLP expertise with product leadership to transform customer experience through automation.

Key Responsibilities

• Strategic Vision: Define and own the long-term product vision and roadmap for voice-based conversational AI solutions, specifically leveraging Google Dialogflow.
• End-to-End Delivery: Lead the full product lifecycle from initial ideation and requirements gathering to deployment, scaling, and continuous optimization.
• Success Metrics: Define project scope and success metrics (e.g., containment rates, sentiment accuracy) to track the business impact of AI deployments.

• NLU Configuration: Provide hands-on guidance on Dialogflow CX/NLU configurations, including the design of intents, entities, and complex fulfillment logic.
• Technical Guidance: Oversee data processing, model development, and deployment (MLOps) to ensure robust and scalable AI performance.
• Cloud Architecture: Navigate cloud-based data architectures to ensure seamless integration of VoiceBOTs into existing ecosystem infrastructures.

• Cross-Functional Management: Lead a specialized team of AI specialists, data scientists, and QA engineers to deliver high-quality conversational experiences.
• Business Alignment: Work closely with Operations, Collections, CRM, and CX teams to translate operational pain points into automated AI workflows.
• Advocacy: Act as the internal champion for AI, educating stakeholders on the capabilities and limitations of conversational technologies.

Requirements

• Professional Tenure: Minimum of 3+ years of work experience specifically within the AI field.
• AI/ML Foundatons: Solid understanding of Machine Learning, Deep Learning, and Natural Language Processing (NLP) methodologies.
• Lifecycle Knowledge: Demonstrated experience in defining project scope, objectives, and technical deployment (MLOps).

• Cloud Platforms: Familiarity with major cloud providers (GCP, Azure, or AWS).
• Preferred Credentials: Fundamental-level certifications such as Azure AI Fundamentals (AI-900) or GCP equivalents are highly considered.
• Tooling: Expertise in Dialogflow CX or similar Conversational AI platforms.

• Leadership: Proven ability to manage cross-functional technical teams in a fast-paced environment.
• Communication: Ability to bridge the gap between complex AI technicalities and business-centric outcomes.
• Agility: A proactive mindset capable of navigating the rapidly evolving landscape of Generative and Conversational AI.