Chethan B

Software Engineer with 3+ years of experience building scalable backend systems, cloud-native platforms, and high-performance full-stack applications across fast-growing product companies.

Currently working at Interview Kickstart, where I build automation systems, scalable APIs, payment platforms, and internal tools that directly improve operational efficiency and business growth.

Some highlights from my journey:

• Revamped the core webinar registration architecture using Django, enabling multi-webinar registrations and improving webinar attendance by 20%+.
• Built automation workflows using Django REST, Celery, AWS Lambda, and EventBridge — saving $2K–$3K/day while achieving 99% synchronization accuracy.
• Developed secure payment and authentication systems powering 35%+ of company transactions using Next.js, Redux, AWS Cognito, and scalable backend services.
• Led end-to-end delivery of projects including referral automation systems and a Discord–Freshdesk integration bot with CI/CD pipelines.
• Consistently delivered 1.5× engineering velocity by effectively leveraging AI-assisted development workflows using Cursor and ChatGPT.

Previously at Vedasis Analytics

• Improved backend performance by 60% through Redis integration, multithreading, and database query optimization.
• Refactored the frontend architecture using reusable components and custom hooks, improving maintainability and development speed.
• Reduced post-deployment production issues by 50% through code reviews and engineering quality improvements.
• Built large-scale Instagram and YouTube scraping systems processing 300k+ data points every month.

Built and launched Logoutloud — a production-ready cross-platform social platform with maps discovery, QR check-ins, push notifications, payments, and geospatial search capabilities.

Technical expertise

Backend: Python, Django, Flask, Node.js, REST APIs, WebSockets, Celery

Frontend: React.js, Next.js, Redux, TypeScript, React Native

Cloud & DevOps: AWS (Lambda, ECS, EC2, S3, SQS, Step Functions), Docker, CI/CD

Databases: PostgreSQL, MySQL, DynamoDB, Firebase, Redis

Other: System Design, Scalable Architectures, AI-assisted development workflows

I enjoy solving engineering problems involving scalability, automation, distributed systems, backend architecture, and product-focused development.

Always open to discussing backend engineering, cloud infrastructure, scalable systems, and AI-powered products.

Software Engineer II at Interview Kickstart (2024-05 – Present)

• Led migration from EC2/Elastic Beanstalk to Dockerized ECS Fargate infrastructure, improving reliability, autoscaling, deployment efficiency, and operational scalability across production services.
• Drove a company-wide PII encryption initiative across 170+ AWS Lambda services and 50+ production workloads, delivering compliance upgrades with zero downtime.
• Architected a distributed event-driven platform using Salesforce Platform Events, AWS Lambda, SQS, Celery, and n8n, processing 20K+ events daily with fault-tolerant delivery, retries, and monitoring.
• Redesigned HubSpot-Salesforce synchronization architecture and successfully migrated 700K+ records while modernizing legacy integrations and improving CRM data reliability.
• Built automated lead recovery systems using Django, Celery, EventBridge, Lambda, and SQS, saving $2K-$3K daily while maintaining 99%+ CRM data accuracy.
• Built a distributed support automation platform using AWS Lambda, DynamoDB, SQS, and DLQs, increasing student query resolution from 30-40% to 90%+.

Founding Engineer at Vedasis Analytics (2023-06 – 2024-04)

• Built the company's influencer marketing SaaS platform from 0 to 1, owning architecture, backend services, frontend applications, database design, and production deployment.
• Led engineering execution through sprint planning, feature prioritization, code reviews, and development workflows, improving delivery predictability and reducing production defects.
• Designed and implemented RBAC, subscription management, and credit-based billing systems that enabled scalable customer onboarding and monetization.
• Established cloud infrastructure on GCP Cloud Run and implemented CI/CD pipelines using GitHub Actions, improving deployment velocity and engineering productivity.
• Improved backend performance by 60% through Redis caching, concurrent processing, and database query optimization.
• Built large-scale Instagram and YouTube data pipelines processing 300K+ records monthly for influencer discovery and analytics.

B.E. in Computer Science and Engineering – SJB Institute of Technology (2019 – 2023)