Top Tech Jobs & Startup Jobs in Mumbai

The Senior Software Engineer will develop scalable applications, mentor juniors, analyze performance issues, and participate in Agile processes, focusing on ownership of product modules.

The SDET will develop and maintain automated testing frameworks, perform white-box testing, ensure test automation in CI/CD pipelines, collaborate on QA practices, and advocate for quality across teams.

The Senior Internal Auditor evaluates business and IT processes, assessing internal controls, performing audits, and recommending improvements to management.

Lead a stream-aligned team in migrating datasets, focusing on hands-on development in Java and React.js, while promoting team autonomy and collaboration. Manage project risks and advocate for best engineering practices.

Serve as Scrum Master for global Agile teams: facilitate ceremonies, remove impediments, coach stakeholders, manage backlogs, track Agile metrics, handle dependencies/risks, and provide status and capacity planning to ensure timely releases.

Support the People & Culture team by managing HR operations, responding to employee queries, maintaining knowledge bases, and assisting with reporting and dashboards.

Develop and improve Sustainalytics digital products using .NET Core and frontend frameworks. Implement solutions, collaborate with global product teams, research enhancements, follow best practices, and resolve reported issues.

The Staff Software Development Engineer will architect business workflows and integrations, guiding technical contributors and focusing on deep enterprise solutions and integrations across multiple teams.

Lead the design and operation of ML systems for data collection and processing. Mentor teams, oversee technical direction, and ensure system reliability and efficiency. Responsible for cloud deployments and integrating advanced AI technologies.

Work with Product and Engineering to prioritize and deliver AI/ML data extraction, enrichment, and collection features. Define backlog, write user stories and acceptance criteria, communicate with stakeholders, track metrics and risks, and support delivery of data pipeline and ML-related services.