Pavan Devulapalle

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).

Experience

Education

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