Product Manager

Location: Bengaluru, India

Department: Product

Experience: 4-8 years

• Real-time product recommendations generated on demand for email and WhatsApp campaigns, at tens of thousands of recommendations per second, straight from live retail data.
• An internal fleet of autonomous AI agents that detect signals in customer data, generate hypotheses, write code, and help resolve customer issues.
• An AI-native way of working across the company, where the first question on any problem is “how would AI help here?”

• Build the product function. Set up how product works here: how problems are discovered, written up, prioritised, tracked in Linear, shipped, and measured. You’ll define the operating rhythm the rest of the team follows.
• Live close to customers. Spend real time with CRM heads, marketing teams, and store operations at some of the region’s biggest retailers. Understand their business pressures, not just their feature requests.
• Solve problems from first principles. Take messy, ambiguous problems (a campaign that underperformed, a flow that confuses users, a gap blocking a customer’s migration) and break them down logically before reaching for a solution.
• Reimagine the flows. Question every inherited workflow. Design AI-native experiences where the product proposes and the marketer decides, rather than copying how CRMs have always worked.
• Work as an engineering peer. Partner with engineers on data models, APIs, scope, and trade-offs. Understand the system well enough to make sound calls and to catch weak ones.
• Use AI as your default tool. Prototype, analyse data, synthesise research, and draft specs with AI, and help the team work the same way.
• Let data decide. Define success metrics before building. Use product analytics and SQL to measure adoption and impact. Retire what doesn’t work.
• Own launches end to end. From spec to rollout to customer adoption, including features that customers need as they move onto Swan 2.0.

• 4–8 years in product management, with meaningful time on CRM, loyalty, marketing technology, or retail / e-commerce products.
• B2B SaaS experience working directly with enterprise customers.
• Technical fluency: comfortable with APIs, data models, and event data; able to write SQL. An engineering background, or years of shipping closely alongside engineers, is a strong plus.
• Hands-on AI usage: you use tools like Claude, ChatGPT, Cursor, or Lovable every day, and can show us something you’ve built, automated, or figured out with them.
• Evidence of process discipline: you’ve run a clean backlog, written specs people actually used, and set up team rituals that stuck.

• Experience with GCC or Middle East retail.
• Loyalty programmes, customer data platforms, or WhatsApp / email / SMS campaign orchestration.
• Built a product function or first product team from scratch.
• Designed LLM features or worked with AI agents in production.

• The chance to build the product function at a company with real customers and real revenue.
• Direct, day-to-day work with the founders.
• AI work that ships to production at retail scale, not in slide decks.
• A lean team where your decisions are visible and matter.