Help design, build and continuously improve the clients online platform.
Research, suggest and implement new technology solutions following best practices/standards.
Take responsibility for the resiliency and availability of different products.
Be a productive member of the team.
Requirements
58 years of overall software development experience
12 years of hands-on experience with AI/LLM, RAG, Generative AI, or Machine Learning in production use cases
Design, develop, and operationalize AI/LLM-driven capabilities within enterprise applications, combining expertise in natural language processing and software engineering to deliver scalable, production-ready AI solutions.
Develop and integrate AI/LLM, RAG, and Generative AI solutions into enterprise systems
Build and expose RESTful APIs for AI-powered functionalities
Collaborate with data scientists, product managers, and engineering teams to deliver AI-driven features
Design and implement data preprocessing and feature engineering pipelines
Deploy, monitor, and optimize AI models in production environments
Enhance performance, scalability, and reliability of AI-integrated applications
Contribute to system architecture and technical design discussions
Write clean, scalable, and maintainable Java code following best practices
Troubleshoot and resolve application and AI-related production issues
Adhere to Agile methodologies and contribute to CI/CD processes
Strong proficiency in Java/J2EE, Spring Boot, and Spring Framework
Experience integrating ML/AI models into Java-based applications (APIs/microservices)
Solid experience in designing and developing RESTful APIs
Strong understanding of data structures, algorithms, and system design principles
Experience with RDBMS (MySQL, PostgreSQL, Oracle)
Familiarity with CI/CD tools such as Jenkins or Azure DevOps
Proficiency in Git or similar version control systems
Working knowledge of Agile frameworks (Scrum/Kanban)
Experience with microservices architecture
Exposure to cloud platforms (AWS, GCP, Azure), especially AI/ML services
Understanding of MLOps practices and model lifecycle management
Bachelor's degree in Computer Science or an equivalent discipline
