Full Stack Engineer
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We’re looking for a Sr. / 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
- Must be residing in Luzon
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