Ayush Jaipuriyar

Full Stack Software Engineer
Bangalore, IN.

About

Highly skilled Full Stack Software Engineer with over 1.5 years of experience specializing in building and optimizing scalable backend systems and dynamic web applications. Proven ability to enhance system throughput by migrating to modern frameworks, reduce latency by up to 90% through caching strategies, and drive significant user engagement with custom translation systems. Adept at leveraging TypeScript, Python, Node.js, NestJS, React, Next.js, Django, and AWS with GitHub Actions (CI/CD) to deliver robust, high-performance solutions.

Work

Healthtrip
|

Full Stack Software Engineer

Noida, Uttar Pradesh, India

Summary

Drove significant performance and scalability improvements for Healthtrip's backend systems and web applications, enhancing user engagement and operational efficiency.

Highlights

Boosted system throughput by 75%, from 120 to 210 RPS, by successfully migrating a legacy PHP backend to a modern NestJS framework, significantly enhancing reliability and scalability.

Engineered and optimized REST, GraphQL, and WebSocket APIs, decreasing average response times by 45%, from 220ms to 120ms, to improve user experience.

Implemented robust Redis caching strategies, resulting in a 70% reduction in database reads and a 90% decrease in query latency, from 300ms to 30ms.

Developed and deployed a custom, multilingual translation system supporting 9 languages, which increased daily active users by 75%, from 5K to 8.75K, across non-English markets.

Created a multilingual Elasticsearch search solution, accelerating query speeds by 60%, from 50 to 80 results per second.

Constructed a high-throughput Kafka notification pipeline capable of processing over 10,000 events daily, reducing P95 latency by 30%.

Automated CI/CD pipelines using GitHub Actions and Docker on AWS (EC2, S3, CloudFront) and Cloudflare, slashing page load times by 50% (from 3.2s to 1.6s) and accelerating deployment cycles from hours to minutes.

AST Consulting
|

Software Developer

New Delhi, Delhi, India

Summary

Contributed to the development of a GenAI SaaS platform, focusing on API development, third-party integrations, and infrastructure optimization.

Highlights

Developed a GenAI SaaS platform from conception using React, NestJS, and MongoDB, integrating advanced AI content generation (OpenAI) functionalities.

Engineered robust REST and GraphQL APIs in NestJS to power AI content generation (OpenAI), scheduling, and analytics, incorporating comprehensive validation, retry mechanisms, and error handling.

Integrated critical third-party services including Stripe/Chargebee for subscriptions and Telegram bot automation, leading to a 25% user adoption rate for bot features.

Optimized MongoDB queries and implemented caching layers, reducing data-heavy dashboard query latency by 44%, from 320ms to 180ms.

Provisioned and managed AWS infrastructure with GitHub Actions CI/CD and CloudFront CDN, reducing image load times by 50%, accelerating deployment cycles by 40%, and achieving a consistent 95%+ uptime.

Education

University of Glasgow
Glasgow, Scotland, United Kingdom of Great Britain and Northern Ireland

M.Sc.

Computer Science

Languages

English

Skills

Languages

Java, TypeScript, Python, C/C++, JavaScript, SQL, Bash, HTML, CSS, Go.

Frameworks

ReactJS, Next.js, Redux, Node.js, NestJS, Express, Flask, Django, Spring Boot, Kafka.

Databases

PostgreSQL, MySQL, NoSQL, MongoDB, Firebase, Redis, Elasticsearch (ELK), BigQuery.

Cloud & DevOps

AWS (EC2, S3, CloudFront, Lambda), GCP, Docker, Kubernetes, Terraform, GitHub Actions, Jenkins, CI/CD, Jira, Cloudflare.

Testing

Jest, JUnit, PyTest, Supertest, Postman.

Projects

LeetCode MCP Server

Summary

Built an MCP server exposing GraphQL endpoints for problems, user profiles, and code submission.

TurboM3U8

Summary

Built a multi-threaded CLI tool for downloading and assembling streaming .m3u8 segments, speeding up downloads.

Near-RT RIC ML-Based Malicious Traffic Detection

Summary

Developed an ML pipeline for real-time traffic analysis with live ingestion/monitoring, achieving 67-73% accuracy and up to 76% F1.

Lenovo Vantage-Linux: ACPI Tuning Utility

Summary

Engineered a command-line Linux utility exposing ACPI performance tuning controls, enabling profile switching and improving battery life by 20-30%.

Ayush Jaipuriyar