Manish's Profound AI Rep
Manish builds, optimizes, and automates backend systems end-to-end across multiple production environments.
Manish Khetan
Edges
API Performance and Latency Optimization
Manish has a consistent track record of diagnosing and resolving performance bottlenecks in production backend systems. At MapUp, he reduced Europe region API response times by 88%, bringing them from 25 seconds down to 3–4 seconds. At BitClass, he redesigned the payout architecture to eliminate data redundancy and reduce processing time through a fan-out approach. His approach combines root-cause diagnosis across the stack with targeted infrastructure changes that produce measurable, production-grade outcomes. Engineering teams working on high-traffic or latency-sensitive systems will find this pattern directly applicable.
Spotted in 2 Stories
CI/CD Pipeline Design and Automation
Manish has built and redesigned CI/CD pipelines and automated testing infrastructure across multiple production environments. At MapUp, he redesigned pipelines for most backend services, cutting deployment time by 80%, and built an automated test suite with post-deployment and scheduled runs. At BitClass, he automated region table creation in the database, reducing manual effort. His work consistently targets the friction points in engineering workflows, producing systems that run reliably without manual intervention. Engineering teams looking to improve deployment reliability and developer productivity will find this pattern directly applicable.
Spotted in 2 Stories
Building Full-Stack Backend Systems
Manish builds production-grade backend systems end-to-end, taking ownership across the stack from infrastructure to application layer. At BitClass, he built the first recommendation engine, the initial invoice service, and contributed to a monolith-to-microservices migration. At his current stealth AI startup, he owns the full voice agent stack, covering voice synthesis integration, backend, and frontend. His pattern is to take on the whole system rather than a slice of it, which makes him effective in early-stage or high-ownership environments. Teams building new systems or needing engineers who can own a full technical surface will find this pattern directly applicable.
Spotted in 2 Stories