Software Developer
Summary
Front-end-heavy software developer role in Singapore: building Angular 19+ applications (AGGrid, NgRx, signals) with Python/FastAPI back-end support and hands-on DevOps work across Docker, Kubernetes, and AWS CI/CD pipelines. Requires 5+ years of development experience and effective use of AI-powered tools like GitHub Copilot.
Master or Bachelor’s degree in computer science/information technology/programming & systems analysis/science (computer studies) faculties.
At least 5 years of software development experience, including 3+ years of front-end development
Front-End Expertise:
- Advanced proficiency in Angular 19+
- Deep knowledge of AGGrid, NgRxstore, Angular signals, and signal store
- Strong sensitivity to design and UX principles
- Experience conducting code reviews and enforcing Angular development best practices
- Ability to ensure consistency and homogeneity across front-end implementations
- Development of automated BDD tests
Back-End Knowledge:
- Experience with Python, REST APIs, and FastAPI
- Ability to develop and maintain back-end services as needed
DevOps & Infrastructure:
- Strong knowledge of Docker, Kubernetes, and microservices architecture
- Experience with GitOps, ArgoCD, Maven, and Git
- Proficiency with CI/CD tools (GitLab, Jenkins, Ansible)
- Familiarity with monitoring and alerting tools (Elasticsearch)
Cloud & Architecture:
- Experience with cloud-native architecture and AWS
- Understanding of distributed systems and scalability patterns
Technical Fundamentals:
- Good knowledge of algorithms and data structures, with strong fundamentals in complexity analysis
- Strong ability to analyze code—understand execution flow and debug even without access to a debugger
- Proficiency with static analysis tools (SonarQube)
- Good knowledge of SQL (PostgreSQL, Redis) or SQL-inspired dialects (e.g., HQL)
- Experience writing and maintaining integration tests
Collaboration Tools:
- Experience with Jira or similar issue-tracking systems
- Commitment to software craftsmanship and DevOps culture
Demonstrated ability to effectively utilize AI-powered tools (e.g., GitHub Copilot) to enhance productivity and problem-solving capabilities
Understanding of AI/ML fundamentals, including prompt engineering, model limitations, and best practices for human-AI collaboration
Experience in evaluating AI-generated outputs for accuracy, security, and alignment with business requirements
Ability to identify opportunities for AI integration and automation within existing workflows and processes