Java Lead

Job description

• Detailed JD below:
• Key Responsibilities:
• Design, develop, and implement Generative AI (GenAI) models using the Gemini AI platform for building intelligent systems capable of processing, analysing, and generating data.
• Develop and optimize machine learning models and pipelines for complex data-driven applications in a microservice architecture.
• Build and maintain Spring Boot microservices that expose APIs for AI/ML models, enabling integration with other services and applications.
• Collaborate with frontend teams to integrate Angular/ReactJS-based UI components, providing a seamless user experience for AI-driven applications.
• Develop interactive, data-driven interfaces using Angular/ReactJS, focusing on real-time updates from backend services and AI model outputs (e.g progress bars, charts, and interactive visualizations).
• Work closely with cross-functional teams (data scientists, backend developers, and business stakeholders) to integrate AI/ML solutions and GenAI features into business-critical systems.
• Work with Google Cloud Platform (GCP) tools and services (e.g. AI Platform, BigQuery, Cloud Functions, Cloud Run) for model deployment, scaling, and management.
• Optimize the performance of AI models and backend services, ensuring scalability and reliability in a microservice architecture.
• Collaborate in designing and implementing AI-driven features using Spring Boot for backend systems, integrating AI models with real-time data processing.
• Create and maintain comprehensive documentation for machine learning models, microservices, APIs, and system architecture.
• Experience with event-driven architectures and working with technologies like Kafka, RabbitMQ, or AWS SQS
• Experience with DevOps practices, including deploying applications in production environments with tools like Terraform, Ansible, or Cloud Build.
• Knowledge of NoSQL databases (e.g MongoDB, Cassandra) and SQL for efficient data storage and retrieval
• Strong knowledge of security best practices in building microservices using Spring Security framework
• Stay up to date with the latest developments in Generative AI, machine learning, microservices, and cloud technologies, and apply them to real-world problems.
• Mentor junior engineers and data scientists, sharing knowledge of AI/ML, microservices, and full-stack development best practices.