Jobs›Full Stack, Pune

Full Stack Engineer

Zoop.one · Pune
वेतन₹12L–18Lसाल, जैसा लिखा है
कहाँPuneMaharashtra
प्रकारFull time3-6 years
Posted14 Oct12 दिन पहले, the company site से
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जो skills माँगे हैं6 लिखे हैं
React.jstailwindcssGo Programming (Golang)NodeJS (Node.js)PythonTypeScript
इस job के बारे में

We're hiring an SDE-2 Full Stack Engineer to build the web experiences adjusters and policyholders use to report, track, and settle insurance claims. You'll spend most of your time on the frontend in React and TypeScript — owning features end to end from design handoff to production — while understanding and contributing to the backend services that power them.

Our claims services are written largely in Go, so Go experience is a strong plus, though solid backend fundamentals in any language are what matter most. We're also building a desktop application in Electron, so Electron experience is a real plus. You'll design APIs alongside backend engineers, reason about data models, and understand how your UI behaves under real production load.

This is a mid-level role for someone who ships independently, raises the bar on frontend quality, and wants to learn the claims domain deeply. The people using what you build are often filing a claim on a bad day or working through a high-volume queue — thoughtful, reliable UX matters here.

What You'll Own

Frontend features across the claims lifecycle: claim intimation, claim status tracking, document and photo upload, adjuster workbench tools, and settlement flows

Translating designs into accessible, responsive, performant UI, and partnering with design and product on usability

API design with backend engineers, and contributions to Go services when a feature needs an endpoint, a data model change, or a fix

Integrations with third-party vendor APIs — surveyors, garages/repairers, hospitals or TPAs, payment gateways, document verification — including error handling, retries, and graceful degradation when a vendor is slow or down

Frontend observability: error tracking, performance monitoring, user-journey analytics, and alerting so we know when a claims flow breaks before customers tell us

Test coverage and observability for everything you ship — unit, integration, and end-to-end

Who You Are

You take a feature from ambiguous requirement to production without waiting to be told each step

You explain technical tradeoffs clearly to engineers, product, and design, in writing and in conversation

You debug across the stack — browser, API, database — and fix root causes, not symptoms

You review others' code generously, ask for review on your own, and help junior engineers level up

Required Qualifications

3+ years of professional software engineering experience, with at least 2 years focused on frontend development

Strong command of React, TypeScript, and Tailwind CSS, including state management, component architecture, and performance tuning

Solid HTML/CSS fundamentals, hands-on Tailwind CSS experience, accessibility (WCAG) awareness, and experience building responsive, cross-browser UI

Working knowledge of backend systems: REST or gRPC API design, relational databases and SQL, authentication/authorization, and how services are deployed and monitored

Hands-on backend experience in at least one server-side language (Go preferred; Java, C#, Python, Node.js, or similar also fine)

Experience writing automated tests at multiple levels

Experience integrating third-party APIs into a product, and instrumenting frontend code with error tracking and performance monitoring

Nice to Have

Experience building or shipping Electron desktop applications: packaging, auto-updates, main/renderer process communication, and native OS integration

Production experience with Go
writing services, concurrency patterns, testing, and the standard toolchain

Experience in another regulated domain (fintech, healthcare, banking) where auditability, data privacy, and compliance shape product decisions

Familiarity with event-driven architectures, message queues, or workflow engines

Cloud platform experience (AWS, GCP, or Azure), containers, and CI/CD

Exposure to applied AI/ML features in product — document classification, intake triage, or LLM-backed assistants

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