An AI system a client's people won't use is a system that failed, however good the model behind it. Design is how we keep that from happening. You shape how people actually experience what we build: the copilots, the tools, the decision dashboards. Your job is to make AI that can be complex, and sometimes intimidating, feel clear, trustworthy, and worth using.
This matters more with AI than with ordinary software. People need to understand what the system is doing, how far to trust it, and when not to. Good design is a large part of how that trust gets built or lost.
The work:
- Run discovery with the client's users to learn how they actually work, not how we assume they do
- Design the interactions and interfaces for our copilots, tools, and decision-intelligence dashboards
- Build and maintain design systems so what we deliver stays consistent and is fast to extend across engagements
- Prototype early, so we test ideas before we spend engineering time building them
- Make clarity, trust, and accessibility first-class: people should understand what the AI is doing and when to rely on it
- Hand the Software Engineer clear, buildable specifications
Where your work ends. You own the experience and the design; the Software Engineer builds it. You work with the Data Scientist on how insight is presented and with the AI Engineer on how copilot and agentic interactions should feel and where to surface the AI's limits.
What success looks like:
- The client's people adopt what we build because it's genuinely usable, not because they were told to
- Complex AI feels clear, and people know when to rely on it and when not to
- A design system that makes each engagement faster and more consistent than the last
- Specs a developer can build from without guesswork
The shared standards, in design terms. The same way of working applies here. Real craft: designs that get built and used, not mockups that sit in a folder. Systems thinking: you design systems, not one-off screens. Quality and security owned by you: usable, accessible, privacy-respecting design built in from the start, and no dark patterns. Built for handover: design systems and documentation the client's own team can maintain.
Tools: Figma for design and prototyping, whatever research methods the engagement calls for, and design-system tooling. Real familiarity with how AI products behave (streaming responses, uncertainty, agentic flows) is a strong plus, because designing for AI is not the same as designing a standard app.
About The Strong AI, and how we work
The Strong AI is an end-to-end AI implementation partner. Clients come to us because most organizations can run an AI experiment, but few can turn it into a system their business depends on. We close that gap. We don't hand over slideware or a notebook; we build systems that work inside a client's business, and where they want it, we run them.
You'll work across engagements and industries, on different problems and often different stacks. We're technology-agnostic: the problem and the client's environment choose the tools, so treat any stack we list as the ground we work on today, not a gate.
We ask for the same way of working from everyone, in the terms that fit the craft:
- Real craft. Designs that get built and used, not mockups that sit in a folder.
- AI literacy. You understand how AI products behave (uncertainty, streaming, agentic flows) and design for it.
- Systems thinking. You design systems, not one-off screens, and see how each piece fits the whole.
- Quality and security, owned by you. Usable, accessible, privacy respecting design built in from the start.
- Built for handover. Design systems and documentation the client's own team can maintain.
Pay: ₹500,000.00 - ₹1,000,000.00 per year
Benefits:
- Flexible schedule
- Work from home
Application Question(s):
- What interests you (in your own words) about working for The Strong AI?
Work Location: Remote
