Product Manager

Bengaluru April 20, 2026 Full Time

[About the role]

We are looking for a highly driven and execution-focused Product professional to own and scale the Swag Store experience. This role sits at the intersection of Product Management, Operations, and AI-driven Analytics, where you will play a key role in driving growth, optimizing user journeys, and improving operational efficiency.

[Key Responsibilities]

Product Management (Execution-Focused)

Partner with the Product Lead to:

Define and prioritise features for Swag Store

Write clear PRDs and requirements, especially for ops, analytics, and tooling features

Drive data-backed decisions around:

Discovery, checkout, rewards, and wallet flows

Experimentation (cashback %, denominations, merchandising)

Ensure features are launch-ready with proper instrumentation and operational playbook.

Product Operations

Own day-to-day operations of Swag Store:

Catalog, pricing, denominations, offers, cashback rules

Campaign setup and monitoring via internal CMS/admin tools

Monitor live product health:

Conversion, GMV, issuance failures, payment issues, reward discrepancies

Act as the primary ops owner for identifying issues and driving resolution

AI-Driven Analytics & Insights

Own Swag Store dashboards and key metrics (funnels, GMV, AOV, reward cost)

Use AI/LLMs to:

Analyze funnels and performance trends

Generate insight summaries and experiment readouts

Detect anomalies and sudden metric changes

Turn insights into clear actions or experiments, not just reports

AI, LLMs & Automation

Actively use and configure LLMs for:

Analytics queries and summaries

Operational checks

Support issue triage and root-cause analysis

Build or manage AI-powered workflows / agents for:

Campaign validation

Offer or cashback misconfiguration detection

Daily or weekly product health summaries

Continuously identify manual workflows and replace them with AI-driven automation

Success Metrics

Improved conversion, GMV, and cashback efficiency

Faster issue detection and resolution

Reduced manual operational effort through automation

Higher experiment velocity and quality of product decisions

[Required Experience]

2-4+ years in Product Management, Product Ops, Analytics, or Marketplace roles.
Strong hands-on experience with AI tools and LLMs (prompting, structured outputs, workflows)
Experience using data to drive product and operations decisions
Comfortable working with CMS tools, dashboards, and internal panels