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Senior Full Stack Java Engineer

Luxoft
Weehawken, USA
Full-time
Senior · 8+ years experience
Discovered 5 days ago
Core Engineering • 8+ 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: o Code generation o Automated testing o Code reviews o Documentation generation o Troubleshooting and incident analysis o 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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Key skills for this role

Core Engineering • 8+ 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: o Code generation o Automated testing o Code reviews o Documentation generation o Troubleshooting and incident analysis o 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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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 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.

Skills

  • Core Engineering • 8+ 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: o Code generation o Automated testing o Code reviews o Documentation generation o Troubleshooting and incident analysis o 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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