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
  • 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

See also

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