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.
