Manager SE(AIQ)
Zyoin
BengaluruOn-siteLead / Manager12–15 yrs
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The job in short
Engineering manager for software and ML/AI data platform team.
PythonJavaJavaScriptTypeScriptScalaNode.jsMySQLDatabricksAWSData science
Details
- Found
- 34 d ago · posted 2026-10-04
- Location
- Bengaluru, KA
Full description
Experience:12- 15 Years
Work Type: Onsite
Employment Type: Full Time
Responsibilities:
• Design and develop software solutions at scale utilizing cloud infrastructure and data services
• that bridge engineering best practices with data science ML/AI services
• Provide thought leadership in innovating and designing future solutions
• Contribute to the product development and platform engineering roadmaps
• Contribute to team awareness and adoption of relevant emerging technologies
• Manage and communicate design elements, project risks and development
• challenges to Leadership
• Write & review high quality code with attention to detail in design, documentation
• and test coverage
• Design for then enforce data security and data privacy mandates in a global
• environment
• Manage a group of developers and help hire new talent
Qualifications
• B.S. in Mathematics, Computer Science/Engineering
• 10+ years of software development, data engineering and/or cloud-based services
• experience
• Strong object-oriented software development background
• Applied software development experience in languages such as Python, Java, Scala,
• JavaScript (Node.js / TypeScript), Shell Scripting
• Applied experience working with a range of data stores and data integration
• technologies (e.g. MySQL, DynamoDB, Athena, Glue)
• Applied experience building APIs or services (e.g. RESTful services)
• Applied experience using unit and integration test frameworks
• Expertise with GIT or other source code repositories
• Demonstrated ability to communicate solutions in terms of technical and functional
• design documents
• Experience building cloud-based software and data solutions utilizing AWS cloud
• services
• Proficiency in building ML/AI data pipelines and automation (e.g. Databricks,
• Sagemaker)
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