SAI NIVED MULA

Chicago,IL

Summary

Backend-focused Full Stack Engineer with 4+ years of experience building high-throughput distributed systems across telecom, healthcare, and financial services. Specialized in event-driven architectures, cloud-native microservices, and performance optimization, with a track record of improving system latency, reliability, and scalability in production environments.

Overview

years of professional experience

Work History

Software Engineer

AT&T

05.2024 - Current

Developed an AI-powered log diagnostics platform (AWS Bedrock + RAG) over 2M+ log entries, surfacing automated root cause suggestions and reducing manual log triage from ~45 min to ~15 min per incident, cutting MTTR by ~50%.
Migrated a critical notification pipeline from synchronous REST to Kafka-based asynchronous processing, eliminating bottlenecks during 5x traffic spikes and reducing end-to-end latency by ~40%.
Designed and evolved microservices handling ~500K daily requests, improving service-to-service latency and fault isolation across critical workflows.
Implemented Resilience4j patterns (circuit breakers, bulkheads, rate limiting) across 6 services, reducing cascading failures by ~25% and improving system stability under load.
Instrumented distributed tracing using OpenTelemetry and Grafana, improving P95 latency by ~20% across 12 microservices.
Drove adoption of event-driven architecture across 3 teams through 10+ design sessions, mentoring 4 junior engineers and establishing best practices.
Built a real-time monitoring dashboard (React + WebSocket) processing ~1,000 updates/sec with virtualized rendering for 10K+ DOM nodes.

Software Engineer (Healthcare)

Accenture

01.2022 - 08.2023

Built cloud-native microservices for clinical data pipelines, processing ~200K+ daily records with HIPAA-compliant data handling and high availability.
Designed Kafka-based ingestion pipelines for patient and clinical events, improving throughput by ~2.5x while ensuring exactly-once processing and data consistency across systems.
Built interoperability APIs (FHIR/HL7) integrating 10+ external systems, reducing data exchange latency and improving reliability of cross-system workflows.
Optimized backend services with Redis and query tuning, reducing response times by ~65% for high-latency clinical data retrieval workflows.
Integrated observability (OpenTelemetry + Grafana) with audit logging and traceability, reducing incident resolution time by ~50% across HIPAA-regulated production systems.

Software Engineer (Financial Services)

IBM

08.2020 - 12.2021

Diagnosed and resolved a 35% P99 latency regression using distributed tracing (Jaeger), eliminating inefficient queries and redundant service calls in a 99.9% SLA financial system.
Optimized PostgreSQL queries on multi-million-row datasets using keyset pagination and composite indexing, improving throughput by 3x and reducing execution time from 1.2s to 400ms.
Designed and implemented a Redis cache-aside strategy for high-traffic APIs (~10K+ RPM), reducing database load by ~60% while maintaining consistency.
Led debugging and resolution of production issues during on-call rotations, improving system reliability and reducing repeat incidents in a 99.9% SLA environment.

Education

Master's - Computer Science

Cleveland State University

05-2024

Bachelor of Technology - undefined

Sreenidhi Institute of Science and Technology

01-2021

Skills

Languages & Backend: Java 17/21, Spring Boot, WebFlux (Reactive), Hibernate, Spring Security (OAuth2/JWT), gRPC
Frontend: React 18, TypeScript, Redux Toolkit, React Query, WebSockets, Tailwind CSS, React Testing Library, Cypress
Cloud & DevOps: AWS (EKS, Lambda, S3, Bedrock), Azure (AKS, App Services), Docker, Kubernetes, Terraform, Jenkins, GitHub Actions

Data & Messaging: Apache Kafka, Redis, PostgreSQL, MongoDB
Observability: OpenTelemetry, Prometheus, Grafana, Jaeger, Resilience4j

Websites

Timeline