React.js Node.js Fullstack Developer - Remote
Role details
Job location
Tech stack
Job description
This is a high-ownership fullstack role. You'll own core product surfaces end-to-end , spanning architecture, backend systems, frontend execution, and production reliability. This is not a feature-factory role. You're expected to make real architectural calls, raise the engineering bar, and move fast through ambiguity.
What You'll Own
-
Design and own end-to-end fullstack systems powering core product workflows.
-
Architect and build clean, scalable backend services and APIs with strong contracts and clear ownership.
-
Develop high-quality, performant frontend interfaces that directly ship to users.
-
Own data modeling and database performance , schema design, query optimization, and long-term maintainability.
-
Partner closely with product and design to translate ambiguous requirements into shipped systems.
-
Set and uphold engineering quality standards through reviews, testing, and technical leadership.
-
Debug and resolve production issues with urgency; improve reliability, observability, and failure modes.
-
Make pragmatic tradeoffs between speed and correctness in a fast-moving AI-lab environment.
Requirements
-
Professional experience building and owning production fullstack systems.
-
Strong TypeScript experience across frontend and backend.
-
Solid backend expertise with Node.js (NestJS strongly preferred).
-
Frontend experience building real products with React.
-
Strong command of PostgreSQL and relational data modeling.
-
Experience designing and maintaining RESTful APIs used at scale.
-
Working knowledge of AWS or comparable cloud platforms.
-
Experience with microservices and/or serverless architectures.
-
Familiarity with Redis, queues, background workers, or async job systems.
-
Strong systems thinking, ownership mindset, and attention to detail.
Nice to Have
-
Experience with CI/CD, infrastructure as code, or DevOps-leaning workflows.
-
Background building cloud-native, production-grade systems from scratch.
-
Exposure to AI-adjacent, data-heavy, or ML-powered products.
-
Prior experience in high-velocity startup or lab-style environments where scope is fluid and impact is high.