Not product managers. Not software engineers. Not AI researchers. People who happen to do all three when the problem demands it — because they care more about solving the problem than about which lane it falls in.
What this role is
Darwinbox is an enterprise HCM platform used by hundreds of large organizations across multiple countries. We're in the middle of a fundamental shift — rearchitecting the product and the company to be AI-native. Not adding AI features to an existing system. Rebuilding how the system thinks, operates, and delivers value.
This role exists because the most significant work in that transformation doesn't fit traditional job boundaries. It sits at the intersection of product thinking, systems engineering, enterprise domain knowledge, and AI — and it requires people who can hold all of that in their head while shipping something that actually works.
You will take ambiguous, high-stakes enterprise problems and turn them into working systems. Some will be customer-facing product capabilities.
Some will be internal operational systems. All of them will require you to think deeply about the realities of enterprise software — permissions, auditability, multi-tenancy, scale, configurability, edge cases — because that's where most "AI-powered" systems quietly break.
What the work looks like
You won't get a detailed spec. You'll get a problem.
It might sound like: "Our customers can't tell whether their employees are actually using the platform — and neither can we." Or: "Implementation consultants spend 40% of their time on work that should be systematized." Or: "This workflow was designed for humans filling forms — redesign it for a world where AI handles 80% of the steps."
Your job is to go from that problem statement to a production system. You'll need to understand the business context, design the solution, build it (using AI-native development workflows extensively), validate it against real enterprise complexity,
📌 AI-Native Systems Builder (Hyderabad)
🏢 Darwinbox
📍 Hyderabad
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