Full Stack Developer (Node.js, TypeScript, AWS, React, NestJS)

Summary

- Key skills: Node.js, TypeScript, NestJS, React, AWS Lambda, DynamoDB, Cognito, REST, GraphQL, Serverless;
- Focus: Full-stack development (Node.js + React), cloud-native architectures, serverless deployments, scalable systems, API design;
- Required experience: 5+ years in full-stack development with strong backend expertise in Node.js and AWS, solid frontend experience with React;
- Experience with modern dev tools (Cursor, GitHub Copilot) and CI/CD pipelines;
- Employment Type: Full-time;
- Location: Hybrid / Remote.

 

Job Description

We're shaping the future of guest experiences in the attractions and entertainment space. Our cloud-native, AI-driven platform serves millions of users with cutting-edge digital media, and we're scaling fast. We're looking for a Full Stack Developer who's passionate about clean code, scalable systems, and modern dev tools like Cursor and GitHub Copilot.

 

What You'll Do

  • Build and scale full-stack apps using Node.js, TypeScript, React, NestJS;
  • Architect cloud-native services with AWS Lambda, API Gateway, DynamoDB, Cognito;
  • Deploy with Serverless Framework, implement CI/CD, and ship features fast;
  • Use Cursor + Copilot to accelerate feature delivery, generate tests, and improve code quality Collaborate closely with Product, Di Architecture teams.

 

Requirements:

  • 5+ years of professional full-stack experience.
    • Strong skills in:Node.js, TypeScript, NestJS;
    • React and modern frontend development;
    • AWS Lambda, API Gateway, DynamoDB, Cognito;
    • REST or GraphQL API design;
    • Serverless deployment, Git workflows, Agile teams;
    • Using Cursor / Copilot responsibly for best-practice coding.

 

Bonus Points

  • MongoDB, PostgreSQL, or hybrid DB architectures;
  • Docker, Kubernetes, Infrastructure as Code (IaC);
  • Jest or equivalent unit testing frameworks;
  • Monitoring tools like Datadog, AWS CloudWatch;
  • Experience with GCP or cloud migration projects;
  • Familiarity with AI media models (e.g. background removal, object segmentation, media enhancement);
  • Background in real-time media or image/video processing pipelines.
Published 24 June
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