Chandra Sahithi

Results-driven AWS & Python Backend Developer with 4+ years of experience building scalable cloud-native applications, serverless architectures, and AI-powered data pipelines. Proven track record at Genpact and Cognizant delivering end-to-end backend solutions using AWS Lambda, S3, DynamoDB, Redshift, and Step Functions. Hands-on expertise integrating Generative AI (LLM/Bedrock/OpenAI) into production workflows, reducing manual effort by up to 40%.

Seeking challenging MNC roles in AWS, Python Backend, or Cloud Development to drive innovation and deliver high-impact solutions.

AWS Developer | Python Backend Engineer - Genpact - Hyderabad, India

(2025-07)

• Integrated Generative AI capabilities (OpenAI & AWS Bedrock APIs) into backend applications, enabling intelligent automation that reduced manual data processing effort by ~40%
• Architected and deployed event-driven serverless pipelines using AWS Lambda, Step Functions, and EventBridge, processing 1M+ records daily with 99.9% uptime
• Developed and maintained 10+ REST APIs in Python, collaborating with frontend teams for seamless UI integration and improved user experience
• Designed scalable data pipelines on S3 and Redshift, reducing report generation time by 45% through query optimization and partitioning strategies
• Built prototype AI-driven solutions and demonstrated GenAI use cases to business stakeholders, accelerating adoption across 3 business units
• Managed IAM roles and security policies ensuring least-privilege access across all AWS services; monitored performance via CloudWatch dashboards

AWS Developer - Cognizant Technology Solutions - Hyderabad, India

(2022-02 - 2025-06)

• Built and maintained cloud-native Python backend services on AWS, supporting applications used by 5,000+ end users across multiple regions
• Implemented Generative AI-based data processing workflows, cutting document processing time from hours to minutes
• Designed YAML-driven dynamic data transformation pipelines, enabling non-technical teams to configure workflows without code changes
• Optimized SQL queries and migrated on-premise workloads to Amazon Redshift, improving query performance by 60%
• Built automated reporting applications generating multi-region reports, eliminating 80+ hours/month of manual effort
• Managed DynamoDB and S3 data storage solutions, ensuring high availability and cost-efficient storage for large datasets

Bachelor of Technology - Computer Science & Engineering - K L University