SDE-2 Fullstack

• *Experience:** 3–5 years

• *Core Focus:** Full\-stack development across search infrastructure, queue systems, and high\-performance UI

• *Tech Stack:** React, TypeScript, TailwindCSS, TanStack Query, Node.js, MongoDB, SQL, Redis, BullMQ

• *Bonus:** OpenSearch/Elasticsearch, Next.js, Framer Motion, circuit breaker patterns, webhooks

About the Role

Join a product team entering its next phase of development and scale. You'll own both sides of the stack, building resilient backend systems that handle large\-scale data and 3rd\-party integrations, and crafting fast, polished frontend experiences that make complex data feel simple. You'll think end\-to\-end: from how data flows through queues to how a user searches, filters, and acts on results in under a second. AI\-driven development is part of how we build, so you'll ship faster using tools like Claude Code, Cursor, and Copilot in your daily workflow.

Why Join

• Ownership: Own a full vertical slice of a product real users depend on daily.
• Growth: Deepen your skills across queue architecture, search performance, and frontend craft in a single role.
• Range: Optimize a backend pipeline in the morning and ship a pixel\-perfect React component in the afternoon.

What You'll Do

• Build and maintain React interfaces with TailwindCSS and TanStack Query for data\-heavy views, with lazy loading, code splitting, and caching for production\-grade performance.
• Design and optimize backend services and database queries for speed and reliability.
• Implement and monitor BullMQ job queues with retries, rate limiting, and dead\-letter handling.
• Integrate 3rd\-party APIs using circuit breakers and graceful fallbacks.
• Use Redis for caching, rate limiting, and cross\-service state.
• Ship features end\-to\-end, API, queue logic, and UI, with monitoring and error handling.
• Collaborate with product and design to turn complex requirements into intuitive experiences.

What We Look For

• You consider the user's experience even when writing backend code, and ask "why does the user need this?" before "how do I build it?"
• You measure before you optimize, logs, metrics, and profiling are your starting point.
• You own problems across the stack instead of saying "that's not my side."
• You use AI tools daily as a multiplier, not a crutch.

Screening questions

More About Yourself

• *Answer using real projects. We're looking for specifics:** actual numbers, real tools and versions, and the messy details. Generic, textbook answers won't help us (or you) here. Where asked, paste the real snippet, error, or metric. How specific and concrete your answers are directly determines whether you're invited to interview. Vague or generic responses won't make the cut.

• *A quick note:** if you let an AI write your answer, expect it to look identical to the 100 other AI\-written answers we'll receive. What makes you stand out is the specific, real detail only you have.