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Shashidhar Alla
Mid-level Software Engineer specializing in full-stack cloud applications
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Backend-leaning full-stack engineer who has shipped both enterprise workflow software and AI-powered document intelligence products. Stands out for combining practical product judgment with strong production debugging skills across Spring Boot, GraphQL, FastAPI, vector search, and RAG systems, and for improving adoption by making AI search experiences intuitive for non-technical users.
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Key Strengths
- Full-stack ownership across React/TypeScript and backend systems
- Strong backend and API architecture judgment
- Production performance tuning in SQL and search systems
- RAG-based AI document search platform development
- GraphQL and data-fetching optimization
- Pragmatic MVP execution in ambiguous zero-to-one projects
- Translating AI capabilities into intuitive non-technical user experiences
- Reliability-focused production monitoring using latency, error rates, retrieval quality, and user feedback
- Security-minded workflow design with backend-enforced approval logic
- Reusable frontend integration patterns and validation/error-state handling
- 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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