As a Senior Full Stack Java Engineer within the US Corporate Loans POD, you will design, develop, and deliver enterprise integration solutions connecting Loan IQ with upstream and downstream platforms. You will leverage modern cloud-native technologies, AI-assisted development tools, and Agentic AI practices to improve software quality, scalability, and delivery velocity.
A key expectation of this role is hands-on experience building AI agents and intelligent engineering solutions that automate and enhance Software Development Lifecycle (SDLC) processes, improving developer productivity and accelerating delivery outcomes.
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 that improve SDLC processes and engineering productivity.
Leverage AI-assisted development tools to accelerate coding, testing, debugging, code reviews, and documentation.
Collaborate with QA, Business Analysts, Product Owners, and Architects to deliver end-to-end solutions.
Conduct code reviews and promote engineering, integration, and cloud best practices.
Contribute to CI/CD automation, release management, and deployment processes.
Design and implement cloud-native integration solutions using Azure services and serverless technologies.
Troubleshoot production issues and optimize application and integration performance.
10+ years of software engineering experience, ideally within 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 application architecture.
Agentic AI & Software Engineering
Experience building AI Agents and Agentic Software Engineering solutions to automate and enhance SDLC processes.
Hands-on experience with Java-based AI frameworks such as Spring AI, LangChain4j, Semantic Kernel, MCP (Model Context Protocol), or similar technologies.
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 and incident analysis
Developer productivity automation
Strong understanding of AI governance, security, observability, and responsible AI practices.
Cloud & Architecture
Hands-on experience with Microsoft Azure services.
Experience building serverless solutions using Azure Functions.
Strong understanding of cloud-native architecture, microservices, and event-driven integration patterns.
Experience with Azure Service Bus, Event Grid, or similar cloud messaging platforms.
Familiarity with Azure OpenAI and AI-enabled cloud architectures is highly desirable.
AI-Assisted Development
Hands-on experience with AI-assisted development tools such as GitHub Copilot, GitLab Duo, Cursor, Windsurf, or similar platforms.
Experience leveraging Generative AI for coding, testing, debugging, documentation, and engineering productivity improvements.
Ability to apply AI tools responsibly while maintaining governance, compliance, security, and quality standards.
DevOps & Tooling
Experience with GitLab CI/CD, Jenkins, Azure DevOps, or similar CI/CD platforms.
Experience with Docker, Kubernetes, and containerized deployments.
Strong understanding of DevOps, automated testing, release management, and deployment automation.
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