Senior Full Stack Java Engineer

Overview

In this role you will design, develop and deliver enterprise integrations connecting Loan IQ with upstream and downstream platforms. You will leverage cloud-native tech, AI-assisted development, and Agentic AI practices to boost software quality, scalability, and delivery velocity. You will build AI-powered agents to automate SDLC processes and collaborate with cross-functional teams to implement end-to-end solutions. This is a hands-on, impact-focused position in financial services engineering with a keen emphasis on modern automation and cloud-native patterns.

Responsibilities

• Design and develop REST APIs, event-driven integrations, and messaging interfaces
• Build and maintain integrations between Loan IQ and enterprise applications
• Design and implement AI-powered agents and workflows to improve SDLC productivity
• Leverage AI-assisted tools to accelerate coding, testing, debugging, reviews and documentation
• Collaborate with QA, BAs, POs, and Architects to deliver end-to-end solutions
• Conduct code reviews and promote best practices in engineering, integration and cloud
• Contribute to CI/CD automation, release management and deployment processes
• Design and implement cloud-native integrations using Azure and serverless tech
• Troubleshoot production issues and optimize performance

Key requirements

• 8+ years of software engineering experience, ideally in Financial Services
• Strong expertise in Java, Spring Boot, REST APIs, and distributed systems
• Experience with Kafka, IBM MQ or similar messaging technologies
• Strong integration experience with Loan IQ, lending, banking, or enterprise platforms
• Deep understanding of API design, system integration, and enterprise architecture
• Experience building AI Agents and Agentic Software Engineering solutions to automate SDLC processes
• Hands-on with Java-based AI frameworks (Spring AI, LangChain4j, Semantic Kernel, MCP) or similar
• Experience implementing RAG, prompt engineering, tool calling, workflow orchestration, and agent-based architectures
• Experience applying AI to code generation, automated testing, code reviews, documentation generation, troubleshooting
• Strong understanding of AI governance, security, observability, and responsible AI practices
• Hands-on Azure services experience, serverless Azure Functions, cloud-native architecture, microservices and event-driven patterns
• Experience with Azure Service Bus, Event Grid or similar
• Familiarity with Azure OpenAI and AI-enabled cloud architectures is desirable
• Experience with AI-assisted development tools (GitHub Copilot, GitLab Duo, Cursor, Windsurf) and Generative AI
• Experience with GitLab CI/CD, Jenkins, Azure DevOps, Docker, Kubernetes and deployment automation

• cross-functional collaboration
• problem-solving
• clear communication
• Java
• Spring Boot
• REST APIs

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