Shashidhar Alla

About

Backend engineer focused on cloud analytics/cost-optimization systems, with strong AWS-centric architecture experience (serverless Lambda, ECS, CloudWatch). Demonstrated deep PostgreSQL/SQLAlchemy optimization at million-record scale (including JSONB/GIN indexing) and built production ML inference services with S3-based model versioning and Airflow retraining pipelines. Also has hands-on multi-tenant SaaS design (separate schemas + RLS) and high-throughput background processing using Celery/Redis with measurable performance gains.

Key Strengths

• Designed serverless Flask backend on AWS Lambda for cost-efficient auto-scaling
• Implemented stateless auth with JWT claims (user_id/role/expiry) for serverless environments
• PostgreSQL/SQLAlchemy performance tuning (indexes, load strategies, query shaping) reducing query latency ~40% at million+ record scale
• Resolved N+1 and excessive DB hits using joinedload/subqueryload/selectinload based on access patterns
• Optimized JSONB filtering with GIN indexes and JSONB operators (@>, ?) for faster queries
• Built and deployed ML inference microservices (Flask/FastAPI) with Docker on AWS ECS and autoscaling via CloudWatch
• Implemented model versioning in S3 with semantic tags and Airflow-based retraining pipeline integrated with CI/CD promotion
• Designed multi-tenant data isolation using separate schemas plus tenant-id scoping and DB-level RLS
• Automated cross-tenant Alembic migrations with schema version tracking and CI/CD integration
• Improved API performance by offloading heavy aggregations to Celery+Redis, cutting API response time ~50% and increasing throughput 3x

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