Allaudheen Shaik

About

Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.

Key Strengths

• Built and operated high-volume payroll processing microservices on AWS (Docker/K8s) with Java/Spring Boot, PostgreSQL, Redis, Kafka
• Diagnosed and fixed peak-time latency/connection pool exhaustion by removing synchronous third-party calls from DB transactions and introducing Kafka-based async processing (reduced latency >50%)
• Shipped AI-powered HR assistant using LLM + RAG with vector DB, citations/confidence scoring, and security controls (reduced support tickets by 40%)
• Designed reliable multi-step agent/workflow systems with planning vs execution separation, strict tool schemas, retries with exponential backoff, circuit breakers, and idempotency
• Strong production engineering practices in Python: clean architecture, typing/validation (mypy/Pydantic), FastAPI async patterns, robust testing and CI, and observability/on-call readiness
• Improved PostgreSQL performance via execution-plan-driven indexing (composite), partitioning by date, and query optimization
• End-to-end delivery of customer-facing onboarding/payroll features with UX and security focus
• Legacy UI modernization (JSP to React) using phased rollout to hit tight deadlines
• Frontend performance and state management improvements (Redux, component refactors, lazy loading/chunked fetching)
• Designing and operating production REST APIs (JWT/API keys, RBAC, versioning, error handling)
• Production reliability practices (unit/integration testing, logging/observability, performance optimization and caching)
• PostgreSQL schema design for high-volume healthcare workflows with indexing and query-plan tuning (EXPLAIN ANALYZE)
• AWS microservices deployment/operations (Docker on EKS, Jenkins CI/CD, CloudFormation, CloudWatch) and scaling incident response (HPA tuning, query optimization)

Experience

Education

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