Product Manager-Application Platform & AI

GREYTIP SOFTWARE PRIVATE LIMITED; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

GREYTIP Software Private Limited in Bengaluru seeks a Product Manager to own the AI platform roadmap, drive onboarding flows, in-app activation and adoption. You will translate user needs into PRDs and maintain a prioritized backlog across modules.

You will shape the AI agent layer, define success metrics, and collaborate with Engineering, Marketing, and Leadership to align roadmaps, measure ROI, and accelerate adoption.

Responsibilities

• Own the product roadmap for platform-level features—onboarding flows, in-app activation and adoption mechanics, cross-module dashboards, and shared platform tooling
• Design and drive PLG loops (self-serve onboarding, in-product upsell/expansion signals, usage-driven activation) that increase adoption and reduce time-to-value across the application
• Write PRDs, user stories, and acceptance criteria grounded in real usage patterns and funnel data — not assumptions
• Maintain a living, prioritized backlog that reflects both stakeholder input and measurable business/growth value
• Own the product vision and roadmap for the flagship AI/agent layer, driving the shift from traditional UI-driven workflows to natural-language and conversational interaction across modules
• Define and prioritize new AI agent capabilities (e.g., conversational search, chat-based workflows, natural language reporting, and task-specific agents) in partnership with engineering and applied AI teams
• Establish a repeatable framework for identifying, scoping, and shipping new agent use cases — from discovery through prompt/response design, grounding sources, evaluation, and rollout
• Define and track AI-specific success metrics: agent adoption, task completion/resolution rate, deflection from traditional UI flows, accuracy/groundedness, and user trust
• Partner with Marketing, OPS/Training, and Leadership to drive internal and external communication, training, and change management around AI adoption

Job description

• Own the product roadmap for platform-level features — onboarding flows, in-app activation and adoption mechanics, cross-module dashboards, and shared platform tooling
• Design and drive PLG loops (self-serve onboarding, in-product upsell/expansion signals, usage-driven activation) that increase adoption and reduce time-to-value across the application
• Write PRDs, user stories, and acceptance criteria grounded in real usage patterns and funnel data — not assumptions
• Maintain a living, prioritized backlog that reflects both stakeholder input and measurable business/growth value
• Own the product vision and roadmap for the flagship AI/agent layer, driving the shift from traditional UI-driven workflows to natural-language and conversational interaction across modules
• Define and prioritize new AI agent capabilities (e.g., conversational search, chat-based workflows, natural language reporting, and task-specific agents) in partnership with engineering and applied AI teams
• Establish a repeatable framework for identifying, scoping, and shipping new agent use cases — from discovery through prompt/response design, grounding sources, evaluation, and rollout
• Define and track AI-specific success metrics: agent adoption, task completion/resolution rate, deflection from traditional UI flows, accuracy/groundedness, and user trust
• Partner with Marketing, OPS/Training, and Leadership to drive internal and external communication, training, and change management around AI adoption

Stakeholder Engagement & Requirements

• Serve as the primary product partner across functions — Product & Engineering, Marketing, OPS/Training, Customer Success, and Leadership
• Facilitate requirement-gathering sessions, workflow audits, and AI use-case discovery to build a ground-level understanding of user needs across modules
• Translate platform and AI requirements into specifications that engineering and design can act on
• Manage stakeholder expectations through clear communication on timelines, trade-offs, and scope decisions

Business Case & Roadmap Development

• Build and present business cases for platform and AI initiatives — quantifying adoption impact, productivity gains, cost-to-serve reduction, and ROI
• Develop a rolling 2-3 quarter roadmap, sequenced by growth impact, AI feasibility, and cross-module dependency
• Align roadmap priorities with leadership and key stakeholders through structured reviews
• Proactively identify where AI and platform-level improvements can reduce manual effort, friction, or support load

Data & Execution

• Define KPIs and success metrics for every initiative — activation rate, adoption rate, agent usage/resolution rate, process cycle time, and time saved
• Use data (funnel, usage, and AI interaction data) to validate hypotheses, measure outcomes post-launch, and inform iteration
• Drive sprint planning, backlog grooming, and cross-functional alignment with engineering, design, and applied AI teams