Read this first.

- You have shipped product design that moved a real metric at scale.

- And you personally build with AI tools: working prototypes, not static frames, and at least one AI-native experience that reached real users.

- If both are true, everything below will read like the role you have been waiting for.

If not, stop here.

- We mean the filter literally: the first interview is you demoing something you built yourself, running live, on your machine.

- Not a case study.

- Not a walkthrough of frames.

- A working thing.

The context:

- Jupiter is a neobank across savings, payments, cards, loans, investments, and insurance, built on RBI-regulated entities with partner banks.

- We have made a company-level bet: AI is not a feature layer on the app, it is the next version of the app.

- A family of production agents already runs inside the business, and the next phase is customer-facing, starting with an agent that replaces our customer servicing stack.

- But most of what users touch this year looks nothing like a chatbot.

- Onboarding.

- Card activation.

- Repayment flows.

- Payment success screens.

- The designers who win here carry both: classic consumer design craft where a two percent funnel lift is real money, and the ability to design for a model whose output is not deterministic.

- And here is the genuinely unsolved part: when an agent moves money, blocks a card, or explains a regulatory protection, the cost of a bad interaction is real financial harm.

- The design patterns for this do not exist yet.

- Confirmation without friction.

- Confidence without overclaiming.

- Disclosure that satisfies a regulator and still reads like a human wrote it.

- You will be creating these patterns, not applying them.

What you'll own:

- Core product surfaces.

- Depending on fit: onboarding, payments, cards, or lending.

- Funnels, friction, comprehension, trust.

- You own design metrics on these surfaces and you move them.

- The AI interaction system.

- A coherent design language for every agentic surface at Jupiter: conversation, streaming, tool-use visibility, citations, confirmations, error and repair states, escalation to humans.

- One system, so a Jupiter agent feels like a Jupiter agent whether it is answering a KYC question or walking someone through a failed UPI transaction.

Trust and safety surfaces:

- The moments where an agent is about to act on money or data.

- Consent, confirmation, and audit patterns that let users move fast and still feel in control.

- This is where design earns its seat in a regulated business.

- Your own leverage stack.

- This is where the 10X comes from.

- You scout, evaluate, and wire together the tools that change what one designer can produce: prototyping setups, agents for design audits and first-pass explorations, transcript review tooling, automated accessibility and consistency checks.

We do not hand you a stack.

- We expect you to bring one, keep upgrading it as the tool landscape shifts month to month, and turn the best of it into the default for the whole design org.

- What you build for yourself often becomes what everyone uses.

How you'll work:

- Your designs ship first as working prototypes you build yourself, with a real model, real latency, real failure modes.

- We test the thing, not a click-through of the thing.

- On agentic surfaces, you write prompts and shape system behavior alongside product and engineering, because the model's behavior IS the interface.

- You read transcripts of real agent conversations the way a traditional designer reads session recordings.

- On classic surfaces, you live in the funnel data and treat every drop-off as a design question before it becomes a growth question.

- And you keep judgment where judgment belongs.

- AI does your grunt work: explorations, audits, first drafts.

- It does not make your calls on hierarchy, trust, or what a moment should feel like.

- The leverage exists to buy you more time on exactly those calls.

What you won't do:

- Hand off static frames and move to the next ticket.

- Design happy paths and let engineering improvise the other ninety percent.

- Split the world into "AI design" and "normal design" and pick a side.

- Wait for a research team to tell you what users felt.

- Ask for a bigger design team before asking whether a tool you could build closes the gap.

What success looks like at six months:

- A metric on a core surface you own has moved, and you can trace exactly why.

- The AI interaction system exists, is documented, and every new agentic surface at Jupiter is built on it.

- At least three of your designs went to users as prototypes you built yourself before an engineer wrote production code.

- Your leverage stack is real and measurable: work that took the team days now takes hours because of tools you brought in or built, and at least two of them have been adopted by other designers.

- When someone at Jupiter asks "how should the agent behave here," they ask you.

- When someone asks "is there a tool for this," they also ask you.

How we'll interview you:

The demo:

- Bring something AI-powered that you designed and built yourself.

- Running, not recorded.

- We will use it together and change things live.

The number:

- Walk us through one classic design project that moved a metric at scale.

- We will push on attribution and what you got wrong.

The stack:

- Walk us through your current tool stack: what you use, what you dropped, and why.

- We are listening for taste and velocity, whether you evaluate tools against real work or against hype.

The teardown:

- We give you a real transcript of an agent conversation that went wrong, and a funnel with a drop-off.

- You tell us what the design should have done in each.

- Same muscle, both worlds.

The build:

- A short working session where you prototype a confirmation flow for an agent action, with AI tools, in front of us.

- We care about how you think with the tools, not pixel polish under pressure.

Logistics:

- Bangalore, in person.

- Five to seven years of experience in consumer product design at scale, fintech a strong plus.

- Reports into the design org, works daily with AI product and engineering leadership.

- 40L to - 70L cash, plus equity, higher for exceptional candidates.