Senior Software Developer

· 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: o   Advanced proficiency in Angular 19+ o   Deep knowledge of AGGrid, NgRx store, Angular signals, and signal store o   Strong sensitivity to design and UX principles o   Experience conducting code reviews and enforcing Angular development best practices o   Ability to ensure consistency and homogeneityacross front-end implementations o   Development of automated BDD tests ·        Back-End Knowledge: o   Experience with Python, REST APIs,and FastAPI o   Ability to develop and maintain back-end services as needed · DevOps & Infrastructure: o   Strong knowledge of Docker, Kubernetes, andmicroservices architecture o   Experience with GitOps, ArgoCD, Maven,and Git o   Proficiency with CI/CD tools (GitLab, Jenkins, Ansible) o   Familiarity with monitoring and alertingtools (Elasticsearch) · Cloud & Architecture: o   Experience with cloud-native architecture and AWS o   Understanding of distributed systems andscalability patterns · Technical Fundamentals: o    Good knowledge of algorithms and data structures, with strongfundamentals in complexity analysis o    Strong ability to analyze code – understand execution flow anddebug even without access to a debugger o    Proficiency with static analysis tools (SonarQube) o    Good knowledge of SQL (PostgreSQL, Redis) or SQL-inspireddialects (e.g., HQL) o    Experience writing and maintaining integration tests ·        Collaboration Tools: o   Experience with Jira or similarissue-tracking systems o   Commitment to software craftsmanship andDevOps culture ·        Demonstrated ability to effectively utilize AI-powered tools (e.g., GitHub Copilot) to enhance productivity andproblem-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 foraccuracy, security, and alignment with business requirements ·        Ability to identify opportunities for AIintegration and automation within existing workflows and processes