Full Stack Developer (Java + Angular + AI/GenAI)

Role: Full Stack Developer (JAVA + Angular + AI)

Location: Toronto, ON - Hybrid (4 Days WFO)

Term: Contract

Job Description:

Key Responsibilities

•Design, develop, and support front end applications using Angular and backend services using Java & Spring Boot.

•Build and maintain scalable RESTful APIs and microservices for enterprise grade banking applications.

•Work closely with product owners, architects, and business stakeholders to deliver best in class digital solutions for RBC.

•Ensure high code quality through automated unit, integration, and functional testing.

•Implement and support CI/CD pipelines, enabling faster and reliable releases.

•Apply secure coding practices, including authentication, authorization, and API security.

•Leverage AI/GenAI tools (e.g., code assistants, test automation, log analysis, productivity accelerators) to improve development efficiency.

•Contribute to cloud native and containerized deployments.

•Actively participate in Agile/Scrum ceremonies and continuous improvement initiatives.

Required Qualifications

Front end

•6–8+ years of hands-on experience with Angular (Angular 10+), TypeScript, HTML, CSS.

•Strong understanding of state management, reusable components, and responsive design.

Back end

•6–8+ years of experience in Java, Spring Boot, and microservices architecture.

•Strong experience 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, OpenShift / Kubernetes.

•Working knowledge of CI/CD tools (Jenkins, Git, Azure DevOps, etc.).

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 (e.g., code generation, refactoring, automated testing).

•Understanding of how GenAI can be applied to productivity optimization, quality improvement, and SDLC acceleration.

•Ability to work with teams adopting enterprise approved AI frameworks and governance models.

•Exposure to AI driven monitoring, analytics, or automation is a plus.