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Project description We are seeking an experienced Senior Full Stack Developer to support the development and enhancement of Communication Surveillance solutions for a leading Banking and Capital Markets client. The role focuses on designing, developing, integrating, and deploying enterprise-grade applications that support the identification and monitoring of regulatory breaches, market abuse, insider trading indicators, collusion, information leakage, and employee misconduct across multiple communication channels, including emails, chat platforms, collaboration tools, and voice transcripts. You need to have a strong hands-on experience in Java, Spring Boot, REST APIs, Microservices, React.js, Node.js, databases, and cloud/DevOps technologies. Knowledge of Machine Learning and AI concepts will be valuable to support the integration and consumption of AI/ML capabilities within Communication Surveillance solutions. You will work closely with engineering teams, business stakeholders, compliance teams, and domain experts to build scalable, secure, and production-ready solutions while adhering to the security, compliance, and governance standards required in highly regulated financial environments. Responsibilities Design, develop, and maintain scalable enterprise applications using Java, Spring Boot, Spring MVC, and Microservices architecture. Develop secure and high-performance REST APIs and backend services. Implement application security using Spring Security and follow enterprise security best practices. Develop responsive and scalable frontend applications using React.js, JavaScript (ES6+), HTML5, and CSS3. Develop and integrate backend and frontend components to deliver end-to-end full stack solutions. Work with Node.js for application development and integration where required. Design and optimize database solutions using Oracle, PostgreSQL, and MySQL. Develop complex SQL queries and perform SQL query optimization to improve application performance. Design and implement scalable microservices and API-based integrations. Build, deploy, and support applications across AWS and/or Azure cloud environments. Containerize applications using Docker and deploy/manage workloads using Kubernetes. Implement and maintain CI/CD pipelines using Jenkins and/or GitHub Actions. Use Git for source code management and follow appropriate branching and development practices. Perform code quality and static code analysis using SonarQube. Collaborate with business stakeholders, compliance teams, and domain experts to translate Communication Surveillance requirements into technical solutions. Integrate application components with AI/ML services and models where required to support surveillance and compliance use cases. Work with data and AI/ML teams to consume and integrate ML model outputs into enterprise applications. Ensure applications are scalable, secure, reliable, maintainable, and compliant with enterprise standards. Troubleshoot application issues, perform root-cause analysis, and provide production support. Participate in code reviews, technical design discussions, performance optimization, and continuous improvement activities. Document technical designs, application architecture, APIs, deployment processes, and operational procedures. SKILLS Must have 712 years of overall IT experience with strong experience in Full Stack application development. Strong hands-on experience with Java 8/11/17+. Strong experience with Spring Boot and Spring MVC. Experience with Spring Security. Strong experience in developing REST APIs and Microservices. Hands-on experience with JPA/Hibernate. Experience with Maven and/or Gradle. Strong frontend development experience with JavaScript (ES6+) and React.js. Experience with Node.js. Good knowledge of HTML5 and CSS3. Strong experience with at least one of Oracle, PostgreSQL, or MySQL. Strong SQL skills, including SQL query optimization. Experience with AWS and/or Azure. Hands-on experience with Docker and Kubernetes. Experience with Jenkins and/or GitHub Actions. Strong understanding of Git and source code management practices. Experience with SonarQube and code quality practices. Working knowledge of Machine Learning concepts, including: oSupervised and unsupervised learning oModel evaluation techniques oData preprocessing and feature engineering Understanding of ML model deployment concepts and MLOps fundamentals. Nice to have Experience in the Banking and Capital Markets domain. Experience with Communication Surveillance, Trade Surveillance, Financial Crime, or Compliance platforms. Understanding of regulatory requirements related to market abuse, insider trading, employee misconduct, and communication monitoring. Experience working with email, chat, voice transcript, and collaboration platform data. Experience with TypeScript. Experience with Python for Machine Learning. Exposure to Scikit-learn, TensorFlow, or .
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