Full Stack Java Engineer

Project Description:

• As an Integration Engineer, you'll drive the design and delivery of integration components that connect Loan IQ with upstream and downstream systems.
• You'll lead technical implementation within your pod, mentor mid-level developers, and leverage modern AI-assisted development tools and cloud-native patterns to enhance productivity, code quality, scalability, and delivery speed.

Responsibilities:

• Lead design and development of REST APIs and messaging interfaces
• Build reusable UI components & frontend frameworks aligned with enterprise standards
• Oversee code quality, conduct peer reviews, and enforce integration best practices
• Collaborate with QA and BA/Product Owner on end-to-end solutions
• Contribute to CI/CD setup and release processes
• Troubleshoot issues and improve performance across interfaces
• Design & implement cloud-native integrations using Azure services & serverless patterns
• Leverage AI-assisted development tools to accelerate code, test, & debug workflows
• Promote AI-based engineering practices & cloud best practices within the team

Mandatory Skills Description:

• 5+ years of backend development experience, ideally in financial services
• Experience with Loan IQ integration, APIs, and data models is essential
• Expertise in Java, Spring Boot, REST, and Kafka / MQ
• Experience in React, JavaScript/TypeScript, HTML5, and CSS
• Strong integration experience with core banking or lending platforms
• Experience with CI/CD tools (e.g., Jenkins, GitLab)
• Cloud & Architecture:
• Hands-on experience with Microsoft Azure services
• Experience building serverless solutions using Azure Functions
• Strong understanding of cloud-native architecture and integration patterns (e.g., event-driven, microservices, API-led connectivity)
• Familiarity with messaging and integration services on Azure (e.g., Service Bus, Event Grid) is a plus
• AI-Assisted Development:
• Hands-on experience with AI-assisted coding tools (e.g., GitLab Copilot, IDE-based copilots)
• Familiarity with using generative AI tools for code generation, unit test creation, debugging, and documentation
• Ability to apply AI tools responsibly to improve developer productivity and code quality while maintaining governance and standards