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Job Description

We're looking for a Full Stack Software Engineer with years of professional software engineering experience who can independently deliver complex features and own technical execution across the stack.

You'll build scalable solutions using Python/Django, Angular/TypeScript, GraphQL/REST APIs, PostgreSQL, and Azure, while contributing to technical design, architecture, mentorship, and engineering improvements.

This is a full-time, night-shift, work-from-home position.

What We're Looking For

  • 4+ years of professional software engineering experience
  • Strong hands-on experience with Python/Django/DRF, Angular/TypeScript, GraphQL/REST APIs, and PostgreSQL
  • Experience with Celery, Redis, Kafka, or similar asynchronous/event-driven technologies
  • Strong understanding of distributed systems, caching, scalable backend architecture, and data modeling
  • Experience with Azure cloud infrastructure and deployment practices
  • Strong knowledge of unit, integration, and end-to-end testing
  • Understanding of application security, performance optimization, observability, and production operations
  • Experience leading technical design and architectural decisions, mentoring engineers, and contributing to cross-team initiatives
  • Bachelor's degree in Computer Science, IT, Software Engineering, Computer Engineering, or a related field

What You'll Do

  • Design and build scalable Django services, REST/GraphQL APIs, Angular components, and PostgreSQL data models
  • Develop asynchronous and event-driven solutions using Celery, Redis, Kafka, or similar tools
  • Improve application performance, scalability, security, testing, monitoring, and reliability
  • Contribute to architecture and technical design decisions across the stack
  • Support reliable deployments and production operations on Azure
  • Lead technical reviews and mentor junior and mid-level engineers
  • Collaborate with Product, Design, QA, and Engineering to deliver high-quality releases
  • Participate in on-call support and drive improvements from production learnings

More Info

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