Sunanda Vasanthi Tata

Software Engineer | California

About Me

MS Computer Science candidate at California State University, Fullerton (May 2026), with 3+ years of industry experience designing and optimizing large-scale distributed systems serving 1.8M+ daily requests. Proven track record improving system performance, reducing operational friction, and shipping reliability improvements across production environments. Expertise in backend architecture, microservices design, system optimization, and LLM-based automation. Strong foundation in data structures, algorithms, and distributed system patterns.

Professional Experience

Pacific Life — Software Engineer Intern

Newport Beach, CA | May 2025 – Dec 2025

Architected validation pipeline reducing manual QA effort by 40%; built REST APIs and React components processing 200K+ monthly portfolio records for 120+ concurrent users
Optimized Kafka stream processing pipeline ingesting 12K+ events/min with multi-layer caching and connection pooling; reduced REST API latency by 24% p99 response time on Kubernetes
Engineered production LLM-based anomaly detection using LangChain agentic chains and Scikit-learn ensemble methods; deployed validation agent eliminating 40% of false positives while maintaining OWASP secure coding practices
Implemented comprehensive test coverage (unit/integration) for React-TypeScript frontend and Spring Boot backend; enforced WCAG accessibility compliance with zero regressions in bi-weekly CI/CD releases

Hitachi Vantara — Software Engineer

Bengaluru, India | Mar 2022 – Jun 2024

Architected Java microservices handling 1.8M+ daily REST API requests on Azure and AWS infrastructure; optimized peak-load latency from 650ms to 500ms via PostgreSQL query tuning and algorithmic improvements, maintaining 99.9% uptime
Engineered NLP-driven entity enrichment pipelines using Spark/PySpark to process web-scraped and partner-sourced data at scale; enhanced information retrieval systems serving billions of daily queries, improving ingestion throughput by 31%
Led design reviews and mentored junior engineers on distributed systems patterns; owned end-to-end feature delivery for 3 major services, deploying bi-weekly releases via Azure DevOps with Terraform IaC, achieving zero high-severity production incidents over 2+ years
Implemented RBAC and OAuth 2.0 authentication across microservices; instrumented with Prometheus metrics and distributed tracing; reduced critical incidents by 35%, improved MTTR by 19%

Accenture — Software Developer

Hyderabad, India | Apr 2021 – Feb 2022

Designed and deployed Python-based REST APIs on a 12-node Kubernetes cluster with PostgreSQL; optimized query performance by 31% via index tuning and algorithm redesign, reducing P95 latency from 800ms to 550ms under peak load
Led technical design reviews for 4-person backend team on API patterns and system reliability; owned L3 incident response, achieving 95% SLA resolution via systematic root cause analysis
Implemented comprehensive unit and integration tests achieving 87% code coverage; established testing best practices, reducing regression incidents by 28%

Projects

Ride-Matching and ETA Engine (Production)

Real-time ride-matching engine with driver-ranking algorithms and geospatial search. Designed event-driven microservices processing driver/rider location updates via Redis Geo indexing, achieving sub-200ms match latency while handling 10K+ concurrent requests.

Tech: Java Python Kafka Kubernetes PostgreSQL Redis Geo

Adversarial Phishing Detection (NLP/LLM)

Fine-tuned transformer models (RoBERTa, T5) on 50K+ labeled phishing samples; engineered LLM-based agentic workflows for adversarial email classification, improving detection F1-score by 14% while maintaining 99.2% precision for production security applications.

Tech: PyTorch HuggingFace Transformers LangChain Python Scikit-learn