Staff Product Designer - India
Staff Product Designer at Syfe, APAC's largest digital wealth platform, owning design direction across multiple product verticals — shaping ambiguous problems, running research, and setting the quality bar using Figma and AI tools for web and mobile apps.
- Compensation
- Not disclosed
- Location
- Gurugram, Haryana, India
- Work setup
- Not specified
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Design
- Posted
Skills
Must have
- 10+ years of product design experience designing and shipping web and Android/iOS apps
- Experience in eCommerce, SaaS or other online businesses
- Sustained ownership of problems spanning more than one product area
- Portfolio showing how you operate in ambiguity — framing, learning, outcomes
- Evidence that your direction has been adopted by other designers or teams
- Strong visual and interaction design skills with excellent judgement in typography, layout, hierarchy, consistency
- High proficiency in Figma for design and prototyping
- Familiarity with AI tools like Claude, Codex, Cursor or Antigravity
- Fluency with research and experimentation — designing studies, reading A/B results honestly
- Exceptional communication and storytelling skills — able to influence senior stakeholders without authority
Nice to have
- Experience in wealth management industry or another regulated domain
- Exposure to online B2C environments with strong understanding of consumer digital experiences
- Experience launching a product or business line that did not exist before
Full description
Syfe is APAC's largest and fastest-growing digital wealth platform, trusted with over US$10 billion in assets. We are fundamentally changing how hundreds of thousands of people across Asia-Pacific build wealth through a holistic approach to managing money rather than just pushing investment products. Backed by world-class investors and recognised as a leader in WealthTech, we are a team of passionate builders creating the future of wealth management.
The Right Profile
- Ambiguity is the job for you, not the obstacle. You take on multiple verticals at once, an idea that's new to Syfe with no precedent to borrow from, or a hard problem that cuts across verticals and belongs to no single team. You don't wait for a product definition to exist - you scope and shape the problem, decide what's worth proving, and make the case for why Syfe should care.
- You find the signal in the noise faster than the people around you. When the team is stuck arguing from opinion, you name the one question that actually decides it, run the study or the experiment that settles it, and come back with a clear read rather than a pile of findings for others to interpret.
- You set direction other senior designers then work from. Your point of view on a space becomes the thing teams design against - not because you own the org chart, but because your framing holds up under pressure.
- You run yourself. Your manager hears what you're working on from you, early enough to help - not because they assigned it to you.
- You raise the ceiling, not just the floor. You produce work that resets what people here think is possible, and you can say precisely what makes it differentiated - beyond "it's usable."
- You use AI to work smarter and solve problems faster. You don't use AI as a substitute for thinking and can tell slop from craft.
- You don't have a fixed design process. You adapt it to the problem in hand and get your hands dirty beyond design - content, research, funnels, metrics. You care about what landed, not just what shipped.
Key Responsibilities
- Own the design direction for multiple product verticals, a new-to-Syfe bet, or a problem that cuts across verticals - setting the vision, principles and quality bar that other designers and teams work from.
- Scope and frame problems before they are defined. Reframe fuzzy asks, articulate what success looks like, name what's explicitly out of scope, and secure alignment before anyone opens Figma.
- Break big work into a sequence of bets that each produces learning, so nothing you own depends on a single all-or-nothing launch. Define what each stage must prove and what would make us stop.
- Decide what the team needs to learn, then run the research or experiment that settles it. Combine qualitative and quantitative evidence and return a decision-ready read, not raw findings.