Job
Description
Key Responsibilities Design, develop, and maintain backend applications using Node.js, ensuring performance, scalability, and security. Build and integrate AI/ML models into applications to deliver intelligent and data-driven functionality. Leverage AWS cloud services including Lambda, SQS, and DynamoDB for building robust, scalable solutions. Work with Kubernetes for containerization and orchestration of microservices (preferred). Design and implement REST APIs and follow microservices architecture best practices. Collaborate with cross-functional teams including data scientists, frontend developers, and DevOps to deliver end-to-end solutions. Utilize and manage MySQL databases, ensuring optimal performance and data integrity. Optimize code and backend services for maximum performance and scalability. Debug and resolve application issues and bottlenecks. Participate in Agile development cycles, contributing to sprint planning, stand-ups, and retrospectives. Stay up-to-date with the latest trends in backend development, AI/ML, and cloud technologies. Mentor and support junior developers, offering technical guidance and code Skills & Qualifications : Minimum 5+ years of experience in backend development, primarily with Node.js. Proven experience in AI/ML integration, understanding model deployment and APIs. Hands-on experience with AWS services including Lambda, SQS, DynamoDB. Strong understanding of microservices architecture and RESTful API development. Experience working with MySQL, including database design, optimization, and Solid knowledge of containerization tools (Docker) and exposure to Kubernetes is a plus. Familiarity with CI/CD pipelines and DevOps practices is advantageous. Strong problem-solving skills, attention to detail, and ability to work in a collaborative environment. Excellent verbal and written communication skills. Ability to work in fast-paced, Agile development Qualifications : Hands-on experience with AI/ML tools/frameworks like TensorFlow, PyTorch, or Sci-kit Learn. Experience in deploying and scaling AI/ML services in cloud-based environments. Exposure to NoSQL databases (e.g., MongoDB) in addition to MySQL (ref:hirist.tech) Show more Show less
