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Pavan Devulapalle
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
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About
Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).
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Key Strengths
- Designed modular, stateless Flask microservice enabling horizontal scaling behind a load balancer
- Strong separation of concerns (routing/business logic/data access) improving maintainability and onboarding
- Database performance tuning with indexing + ORM strategy changes (e.g., selectinload, SQLAlchemy Core)
- Reduced slow endpoint latency from ~2s to <200ms via composite indexes and query rewrite
- Integrated ML/GenAI into backend using SageMaker endpoints and Bedrock LLM APIs with asynchronous orchestration
- Designed multi-tenant data isolation with schema-per-tenant and dedicated Postgres instances for large tenants
- Optimized high-throughput background processing by deduping external calls, TTL caching, and splitting queues; reduced processing from minutes to seconds
Reference Highlights
- End-to-end innovation in product building
- Strong ownership; builds products from 0 to 1
- Thorough understanding and hands-on experience with Python/Flask/SQLAlchemy
- Successfully streamlined data retrieval
- Able to handle large-scale data
- Designed lightweight microservice architecture to integrate services
- Designs low-latency APIs
- Effective cross-team collaboration (worked with 20+ teams)
- Clear communication of needs with each team
- Clearly defines and divides ownership boundaries
- Handles complex problem-solving/debugging very well under deadlines
- Structured approach: analyze situation, prioritize tasks, iterate using Agile
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