Senior Software Developer
Summary
Senior developer building scalable front-end apps with Angular 19+, NgRx, and AGGrid, plus Python back-end services and AWS cloud-native systems.
Master's or Bachelor’s degree in Computer Science/Information Technology/Programming & Systems Analysis/Science (Computer Studies) faculties.
At least 12 years of software development experience, including 8+ years of front‑end development.
Front‑End Expertise
- Advanced proficiency in Angular 19+
- Deep knowledge of AGGrid, NgRx store, 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
AI & Machine Learning
- 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