Role Overview:

As an AI & Data Product Manager for Core Platforms at this company, you will be instrumental in building a common AI + Data platform that supports various products related to test prep, learning, counselling, and growth. This role is central to the platform's operations and you will primarily focus on AI-first products such as AI Voice Counsellors / Voice Bots, Doubt Solvers, Agentic frameworks, and Data-driven PLG systems. It is important to note that this role is not a feature PM role but a 0 1 and 1 10 platform role where dealing with ambiguity, real stakes, and speed is crucial. If you thrive on creating new solutions and enjoy working in a dynamic environment, this role is perfect for you.

Key Responsibilities:

• Define the product vision and roadmap for core AI and data layers
• Identify opportunities for AI-first products by addressing business problems
• Maintain a balance between short-term impact and long-term platform thinking
• Design and evolve the core data architecture supporting analytics, PLG, and AI systems
• Own data planning including event schemas, source-of-truth definitions, and data contracts
• Manage data marts, feature stores, and semantic layers for various business and AI use cases
• Establish canonical metrics, funnels, and KPIs across products and teams
• Ensure data reliability, timeliness, explainability, and usability
• Collaborate with engineering to enforce data quality, lineage, and governance standards
• Bridge the gap between data, AI outputs, user behavior, and data systems
• Build and ship AI products that function effectively in production using LLMs, RAG systems, Voice AI, and Agentic workflows
• Collaborate with cross-functional teams to deliver AI systems efficiently
• Focus on catering to the masses with real internet challenges while developing AI products
• Partner with different departments to identify use cases and convert ideas into actionable plans
• Drive PLG using data flows to enable activation nudges, personalized journeys, and conversion & retention loops
• Design metrics, experimentation frameworks, and feedback loops to enhance PLG
• Conduct experiments, measure outcomes, and iterate quickly to achieve desired results
• Take ownership of outcomes and drive continuous learning and improvement

Qualifications Required:

• 5 to 9 years of Product Management experience
• Strong background in Data Products, AI Products, or Platform Products
• Hands-on expertise in LLMs, prompts, RAG, embeddings, ML/AI product lifecycle, data pipelines, event design, data modeling, data marts, analytics, and metrics design
• Ability to work in high ambiguity and low structure environments
• Experience with Voice AI / Conversational AI is preferred
• Prior experience in EdTech, SaaS, Media, Consumer Tech, or PLG businesses is advantageous
• Startup or scale-up experience is a plus

Additional Details:

N/A Role Overview:

As an AI & Data Product Manager for Core Platforms at this company, you will be instrumental in building a common AI + Data platform that supports various products related to test prep, learning, counselling, and growth. This role is central to the platform's operations and you will primarily focus on AI-first products such as AI Voice Counsellors / Voice Bots, Doubt Solvers, Agentic frameworks, and Data-driven PLG systems. It is important to note that this role is not a feature PM role but a 0 1 and 1 10 platform role where dealing with ambiguity, real stakes, and speed is crucial. If you thrive on creating new solutions and enjoy working in a dynamic environment, this role is perfect for you.

Key Responsibilities:

• Define the product vision and roadmap for core AI and data layers
• Identify opportunities for AI-first products by addressing business problems
• Maintain a balance between short-term impact and long-term platform thinking
• Design and evolve the core data architecture supporting analytics, PLG, and AI systems
• Own data planning including event schemas, source-of-truth definitions, and data contracts
• Manage data marts, feature stores, and semantic layers for various business and AI use cases
• Establish canonical metrics, funnels, and KPIs across products and teams
• Ensure data reliability, timeliness, explainability, and usability
• Collaborate with engineering to enforce data quality, lineage, and governance standards
• Bridge the gap between data, AI outputs, user behavior, and data systems
• Build and ship AI products that function effectively in production using LLMs, RAG systems, Voice AI, and Agentic workflows
• Collaborate with cross-functional teams to deliver AI systems efficiently
• Focus on catering to the masses with real internet challenges while developing AI products
• Partner with different departments to identify use cases and convert ideas into actionable plans
• Drive PLG using data flows to enable activation nudges, personalized journeys, and conversion & retention loops
• Design metrics, experimentatio