Full-Stack Software Engineer with Distributed Systems Expertise

Kiruthiga Muralidharan FULLSTACK SOFTWARE ENGINEER

*********@*****.*** Phone: 408-***-**** Location: Newark, CA 94560 LinkedIn Github SKILLS

Languages: Java, Python, Go, Lua, JavaScript, TypeScript, SQL, HTML5/CSS3 Frontend: React.js, Redux, Next.js, WCAG 2.1 (A11y), SASS Backend: Node.js, Spring Boot, Generative AI (LLM API Integration), Vector Embeddings Testing & Quality: Mockito, JUnit, SonarQube, TDD Networking & APIs: REST, gRPC, WebSockets, HTTP/2, JSON-RPC Cloud & DevOps: AWS (EC2, S3, SQS, Lambda, DynamoDB), Kubernetes, Docker, Terraform, Jenkins Specialized: Adobe Experience Manager (AEM), Distributed Systems, Microservices, Redis Lua Scripting EXPERIENCE

Senior Software Engineer, Tata Consultancy Services Jun 2022 – Jul 2024

• Spearheaded the development of scalable enterprise solutions by integrating React-based Single Page Applications (SPA) with Java backend services, ensuring modularity and high performance in a complex distributed environment.

• Optimized system-wide data delivery by fine-tuning multi-tier caching strategies and dispatcher-level configurations, resulting in a 15% increase in server throughput and a 25% reduction in page load latency.

• Developed a Proof of Concept (PoC) for automated audience segmentation and personalized content delivery, achieving a 12% projected increase in user conversion rates.

• Acted as the primary technical lead during a 3-month on-site residency, translating complex business requirements into architectural roadmaps and streamlining the requirement-to-deployment pipeline by 40%. Application Development Team Lead, Accenture Jan 2020 – Jun 2022

• Diagnosed and resolved critical JVM memory leaks and heap space issues during high-volume data ingestion, performing Root-Cause Analysis (RCA) to ensure 99.9% system stability.

• Managed the automated creation of 10,000+ product pages using high-concurrency scripts, achieving a 99.99% data synchronization success rate across distributed Author/Publisher server clusters.

• Architected reusable backend components using Java, Node.js, and React, reducing code redundancy by 40% and improving overall system maintainability.

• Automated critical operational tasks, including offline compaction and SSL renewals, enhancing proactive server maintenance to achieve 99.9% system uptime and eliminate manual overhead for global production environments.

• Implemented advanced multi-tier caching strategies and CDN configs, resulting in a 30% improvement in page load latency for global users while ensuring zero-downtime deployments through optimized CI/CD release workflows. Senior Systems Engineer, Infosys Jul 2016 – Jan 2020

• Developed custom Java-based workflows to process XML business data, reducing manual localization cycles by 60% and ensuring 100% data consistency across global site copies.

• Architected modular backend services and reusable API components using Java and OSGi to support high-traffic global operations; reduced code redundancy by 40% and accelerated new feature development speed by 35%.

• Engineered WCAG-compliant (AODA/WCAG 2.1) reusable UI components and templates, ensuring 100% accessibility compliance for global web properties while improving SEO rankings. EDUCATION

Master of Science in Computer Science, Northeastern University, USA; CGPA: 3.958/4 Sep 2024 – Apr 2026 Bachelor of Engineering in Computer Science, Anna University, India; First Class with Distinction Aug 2012 – May 2016 Certifications: 2x Certified AEM Sites Developer Expert, Microsoft Azure Fundamentals PROJECTS

• High-Scale E-Commerce Flash Sale System: Architected a distributed pipeline in Go utilizing Redis Lua scripting for atomic inventory checks to ensure 99.9% consistency under "thundering-herd" surges while integrating AWS SQS to decouple services and maintain low P99 latency during high-concurrency spikes.

• Spendly - Personal Finance Tracker: Engineered a responsive React SPA and Node.js/Express RESTful API using Prisma ORM for persistent storage and JWT for secure authentication alongside interactive dashboards integrated with external Stock Market APIs.

• Intelligent Systems & Predictive Modeling: Developed a Stacking Ensemble model (XGBoost + ANN) achieving a 0.88 R for health cost prediction and engineered a Fraud Detection pipeline using SMOTE to optimize for 0.918 Recall and 0.97 ROC-AUC.

• AI-Powered Semantic Matching Platform: Architected a Flask-based matching engine integrating Gemini API for 768-dimensional semantic embeddings with NumPy-implemented cosine similarity algorithms, achieving 76% average match accuracy while engineering a hybrid LLM pipeline and JSON-based caching strategy to reduce API latency by 85%

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