Top Tech Jobs & Startup Jobs in Mumbai

The Network Support Engineer is responsible for troubleshooting, resolving network issues, maintaining network performance, and supporting customers in a 24/7 environment.

The role involves ensuring software quality through testing strategies, automating test cases, and mentoring fellow QA Engineers. You will analyze and document defects while promoting best practices across the organization.

As a Software Engineer at Kyndryl, you will design, develop, and implement software solutions, ensuring code quality and system integration, while collaborating on complex projects. You will also have opportunities for career advancement.

As a Senior Network Support Engineer, you will install, maintain, and troubleshoot complex computer networks. Responsibilities include monitoring network performance, resolving issues, implementing security policies, and providing user support in a multi-vendor environment.

Develop and deploy Generative AI solutions, engage with customers, and integrate AI/ML into cloud environments, requiring strong expertise in AI technologies and hands-on experience.

The Data Scientist will develop and implement GenAI solutions, focusing on NLP and AI technologies. Responsibilities include working on LLM projects and collaborating with teams to integrate AI solutions into cloud environments.

Design and implement network solutions, troubleshoot issues, provide support for network services, manage multiple projects, and coordinate installations.

The QA Engineer will manage manual and automated testing, collaborate on application design, mentor junior developers, and provide solutions using microservices.

The Senior Network Support Engineer will install, maintain, and troubleshoot networks, collaborate with teams, monitor performance, and support users in a 24x7 environment.

Lead design, development, and deployment of Generative AI and LLM solutions across cloud environments. Engage clients, build POCs/POVs, translate business needs into data problems, develop and validate models, and operationalize models with MLOps and DevOps practices while ensuring data governance, security, and domain-aligned solutions.