Group Product Manager - AI
IndiaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 10+ years of product management experience, including 3+ years leading PMs or multi-product portfolios.
- Required Skills
- Product ManagementCRMSaaS
Requirements
- 10+ years of product management experience, including 3+ years leading PMs or multi-product portfolios.
- Proven experience building AI-driven, automation, SaaS, CRM, or platform-based products at scale.
- Strong understanding of AI systems including LLMs, agents, RAG pipelines, prompt management, model evaluation, and orchestration.
- Demonstrated ability to translate complex AI capabilities into intuitive, production-ready user experiences for non-technical users.
- Strong technical fluency with the ability to collaborate deeply with engineering teams on system design and trade-offs.
- Experience defining and scaling product metrics such as activation, retention, monetization, adoption, and quality signals.
- Strong leadership and mentoring experience managing product managers and cross-functional teams.
- Excellent communication skills with the ability to influence stakeholders across technical and business functions.
- Strong ability to operate in ambiguity, prioritize effectively, and bring structure to fast-evolving product areas.
- Experience building products for SMBs, agencies, or B2B SaaS ecosystems.
Responsibilities
- Define and drive the end-to-end product vision, strategy, roadmap, and success metrics for a multi-layered AI product portfolio.
- Lead and mentor a team of product managers across AI domains including Voice AI, Conversation AI, AI Employee, Ask AI, Knowledge Base, AI Studio, Workflow AI, and other emerging capabilities.
- Build a unified AI platform layer including shared primitives such as agents, orchestration, memory, evaluation systems, permissions, analytics, and safety frameworks.
- Own product strategy for AI monetization, packaging, pricing models, usage-based billing, activation, retention, and expansion.
- Drive adoption and activation across SMBs and agencies by simplifying onboarding, setup flows, templates, and AI-driven workflows.
- Partner closely with engineering to balance trade-offs across latency, cost, model quality, scalability, reliability, and user experience.
- Establish strong evaluation frameworks for AI quality, including hallucination rate, task success, response quality, and customer satisfaction metrics.
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