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Senior Backend Engineer (Java / Cloud)

PRI Global
Vancouver, British Columbia, CAPosted April 24, 2026

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JavaSQLAngularSpringAWSAzureDockerKubernetesJenkinsRESTgRPCCI/CD

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Job Description

Seeking a Senior Software Engineer to contribute to the design and development of high-performance, cloud-ready systems. This role is hands-on and also involves mentoring peers, participating in architecture discussions, and driving engineering excellence across the team.

Key Responsibilities

  • Design and develop backend services using Java, leveraging frameworks such as Spring and gRPC
  • Take ownership of assigned technical components and ensure timely, production-ready delivery
  • Collaborate with cross-functional teams to define requirements and participate in architecture and design discussions
  • Work with CI/CD pipelines (Jenkins), Kubernetes, and containerized deployment environments
  • Support cloud migration and modernization initiatives
  • Participate in code reviews and enforce engineering best practices and standards
  • Drive automation in testing, deployment, and validation processes to improve system reliability and efficiency

Required Skills

  • Strong expertise in Java development
  • Hands-on experience with Spring Framework, gRPC, and related technologies
  • Experience with unit testing frameworks such as JUnit, Mockito, or EasyMock
  • Strong knowledge of SQL and experience working with Oracle databases
  • Experience building high-performance and scalable applications
  • Strong analytical and problem-solving abilities
  • Ability to manage multiple priorities in a fast-paced environment
  • Experience with testing tools such as REST Assured, Selenium WebDriver, etc.
  • Experience with Docker and Kubernetes
  • Familiarity with cloud platforms such as AWS, Azure, or PCF
  • Exposure to frontend frameworks such as Angular (preferred)
  • Bachelor’s degree in Computer Science or related field preferred
  • Experience in AI/ML platform environments or decisioning systems
  • Background in cloud-native architecture and distributed systems

The team focuses on AI model deployment and improving the model deployment pipeline, contributing to critical initiatives aligned with the organization’s cloud modernization roadmap.

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