Gain hands-on experience building applications using modern AI-driven software engineering practices, including Generative AI, Agentic AI, and AI-assisted development workflows.
Develop new features and enhance existing applications using modern programming languages, frameworks, and cloud technologies.
Participate in coding, testing, debugging, and troubleshooting activities, while gaining hands-on experience with engineering best practices
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Provide advanced support and troubleshooting for data pipelines, ETL/ELT processes, and data integration workflows across cloud and on-prem environments.
Enhance and mentor others in organizational, communication, and analytical skills, fostering a collaborative and data-driven engineering culture.
Gain exposure to the end-to-end machine learning lifecycle, from experimentation to production, by enabling robust and scalable data access for model training and inference.
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Security & Governance: Implement enterprise security controls on-site, including IAM policy management, network security groups, encryption standards, and local regulatory compliance rules.
Operations & Troubleshooting: Perform real-time technical troubleshooting, root-cause analysis (RCA), and operational support directly within the client environment.
Client Engagement: Communicate technical progress, document architecture setups, and provide technical advisory to local stakeholder teams.
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