Full Stack Java Developer- Angular, Spring Boot, AI

Job Title: Full Stack Java Developer - Angular, Spring Boot, AI

Location: Toronto, ON (Hybrid)

Experience: 6–8+ Years

Key Responsibilities

• Design, develop, and maintain front-end applications using Angular and backend services using Java & Spring Boot.
• Build and support scalable RESTful APIs and microservices for enterprise-grade banking applications.
• Collaborate with product owners, architects, and business stakeholders to deliver high-quality digital solutions.
• Ensure code quality through automated unit, integration, and functional testing.
• Implement and manage CI/CD pipelines for efficient and reliable deployments.
• Apply secure coding practices, including authentication, authorization, and API security.
• Leverage AI/GenAI tools (code assistants, automated testing, log analysis) to enhance development productivity.
• Contribute to cloud-native and containerized deployments.
• Actively participate in Agile/Scrum ceremonies and continuous improvement initiatives.

Required Qualifications

Front-End Development

• 6–8+ years of hands‑on experience with Angular (10+), TypeScript, HTML, and CSS.
• Strong understanding of state management, reusable components, and responsive design.

Back-End Development

• 6–8+ years of experience in Java, Spring Boot, and microservices architecture.
• Strong expertise in building RESTful APIs and backend services.
• Hands‑on experience with Kafka or other messaging systems.
• Solid experience with SQL databases (PostgreSQL, Oracle, MySQL).

DevOps & Cloud

• Experience with Docker, Kubernetes / OpenShift.
• Working knowledge of CI/CD tools such as Jenkins, Git, and Azure DevOps.

Security

• Experience with OAuth 2.0, OIDC, JWT, SSL/TLS, and enterprise API security standards.
• Familiarity with secure banking application development.

AI / GenAI Expectations

• Hands‑on exposure to AI‑assisted development tools (code generation, refactoring, automated testing).
• Understanding of how GenAI improves productivity, quality, and SDLC efficiency.
• Ability to work within enterprise AI frameworks and governance models.
• Exposure to AI‑driven monitoring, analytics, or automation is a plus.

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