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We are seeking a Solutions Architect with a strong foundation in Java, Microservices Development, and exposure to Artificial Intelligence (AI) / Machine Learning (ML). In this role, you will contribute to the design, development, and implementation of scalable, high-performance applications, while supporting the integration of AI/ML capabilities into enterprise systems. You will collaborate with cross-functional teams and support architectural initiatives within a dynamic financial services environment
Job Responsibility
Assist in designing scalable, high-availability Java microservices and supporting the integration of AI/ML components into enterprise applications
Develop clean, maintainable, and efficient code for microservices, APIs, and AI-enabled features using Java and related technologies
Monitor system performance and help identify and resolve performance bottlenecks to ensure reliability and scalability
Collaborate with senior architects and engineers to implement best practices in microservices architecture and AI integration
Follow established coding standards, security guidelines, and participate in code reviews to maintain high-quality deliverables
Support debugging and resolution of technical issues across applications, including microservices and AI integrations
Work closely with developers, data scientists, and product teams to build and deliver integrated solutions
Stay current with emerging technologies in Java, microservices, and AI/ML
proactively suggest improvements and enhancements
Contribute to technical documentation, including APIs, system designs, and operational processes
Requirements
5+ years of software development experience with hands-on work in Java, microservices, and enterprise applications
Proficiency in Java (JDK 8+/11+), Spring Boot, and REST APIs
Familiarity with Spring Cloud, Hibernate, Gradle/Maven
Working knowledge of Python
Understanding of microservices architecture, distributed systems, and messaging systems (Kafka, RabbitMQ)
Experience with API design and tools like OpenAPI/Swagger
Basic understanding of AI/ML concepts and exposure to integrating models or APIs into applications
Familiarity with cloud platforms (AWS, Azure, or GCP), Docker, and Kubernetes basics
Experience with relational (Oracle, PostgreSQL) and/or NoSQL databases (MongoDB, Cassandra)
Understanding of CI/CD pipelines and version control systems (e.g., GitHub)
Strong analytical and troubleshooting skills with attention to detail
Ability to communicate technical ideas effectively with team members
Bachelor’s degree in Computer Science, Engineering, or related field
Nice to have
Exposure to AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Understanding of real-time processing tools (e.g., Apache Spark or Flink)
Experience in financial services or regulated environments
Interest in learning MLOps and AI-driven development practices