Software Engineer · Backend Systems · Full-Stack Products · AI Workflows

I build backend and full-stack systems where reliability, performance, and clear user workflows matter.

• Design REST APIs, services, and data workflows for production-facing applications
• Build full-stack features using Java, Spring Boot, React, Angular, Apex, and LWC
• Work with Kafka, Redis, PostgreSQL, Docker, CI/CD, and monitoring pipelines
• Improve system performance, reduce failures, and make high-volume workflows easier to maintain

• Engineered backend services and REST APIs using Salesforce Apex and Lightning Web Components
• Supported multi-participant intake workflows handling 1K+ records per transaction
• Built bulk-safe validation and async processing flows, reducing retries and governor-limit failures by 40%
• Resolved SOQL, heap, and workflow issues, reducing recurring production incidents by 30%

• Built customer onboarding and profile-management features using Java, Spring Boot, Hibernate, Angular, and REST APIs
• Designed Controller-Service-DAO layers with reusable business logic and request validation
• Improved API latency by 35% using Redis caching, query optimization, batching, and connection pooling
• Maintained 95% unit test coverage with JUnit and Mockito across backend services

Spring Boot · React · Kafka · PostgreSQL · OpenCV · FFmpeg

Built a real-time sports video intelligence system that detects scoreboard changes, processes live event streams, and generates highlight clips from sports footage.

• Designed Kafka-based event pipelines for real-time score and event processing
• Built Spring Boot APIs and PostgreSQL storage for structured highlight records
• Created a React dashboard for viewing events, generated clips, and system output
• Used OpenCV, FFmpeg, and custom digit classification for video-based event detection

Go · Python · FastAPI · Docker · LLM · OAuth2

Built an AI-assisted scheduling system that converts user goals into structured plans and calendar-ready tasks.

• Designed a Go backend with a FastAPI orchestration layer for workflow execution
• Integrated LLM workflows to generate structured schedules from natural-language input
• Added OAuth2-based calendar integration and validation logic for conflict-free planning
• Dockerized the system for repeatable local development and service iteration

Python · PostgreSQL · Docker · Prometheus · Grafana · CI/CD

Built a production-style monitoring dashboard for logs, metrics, alerts, and service health signals.

• Modeled PostgreSQL schemas for incident history, metrics, and performance trends
• Built dashboards to detect latency spikes, failed jobs, and backend reliability issues
• Added Dockerized setup and CI/CD-ready checks for repeatable deployment workflows

Languages:        Java, Python, Go, SQL, JavaScript, TypeScript
Backend:          Spring Boot, Hibernate/JPA, REST APIs, Microservices, Apex
Frontend:         React, Angular, Lightning Web Components, HTML/CSS
Data Systems:     PostgreSQL, MySQL, MongoDB, Redis, Kafka, ETL
Cloud/DevOps:     AWS, Docker, Kubernetes, CI/CD, Jenkins, Git
Practices:        OOP, Data Structures, Algorithms, Testing, Debugging, Monitoring
AI Workflows:     LLM APIs, FastAPI orchestration, AI-assisted automation

• Reduced governor-limit failures and job retries by 40%
• Improved API latency by 35% under production workloads
• Reduced recurring production incidents by 30%
• Maintained 95% unit test coverage across backend services
• Built workflows supporting 1K+ records per transaction and 10K+ record datasets

I’m currently focused on backend engineering, distributed systems, full-stack product development, and AI-assisted workflows. I like building systems that are practical, testable, and easy to explain from API design to database behavior to production debugging.

📫 Email: naitikshah1812@gmail.com
🔗 LinkedIn: https://www.linkedin.com/in/naitik1008
🌐 Portfolio: https://my-portfolio-khaki-eight-80.vercel.app