Lohith Surisetti
Full Stack Engineer | Scaled @Uynite to 100k+ users | Spring Boot | Kafka | MuleSoft | AI
- Role
- Application Developer at Uynite,inc
- Location
- Chicago, IL, US
- LinkedIn followers
- 500 followers
About Lohith Surisetti
I\'m a backend and platform engineer with over 5 years of experience building scalable systems, data pipelines, and AI/LLM integrations across social media domains.• At Uynite, I led backend development for both the core app and GeoKiks, a short video platform, scaling them to 100k+ users through a modular microservices architecture. Independently built and maintained 10+ microservices, implemented real-time systems using Kafka, and integrated Python ML models for content moderation.• At InvenioLSI, Contributed to the Intrack project, a workflow and timesheet management platform for tracking 900+ employee timesheets, project allocations, and managerial hierarchies. Built REST APIs using Spring Boot and MuleSoft Anypoint Platform, optimized backend queries, and delivered 5+ MuleSoft-based POCs for automation and microservices adoption.Also participated in a MuleSoft Hackathon, focusing on API-led integration for workflow modernization.My core skills include Java, Spring Boot, Python, Kafka, MongoDB, AWS, and building high-performance backends, ML pipelines, and data systems that scale. I’m especially strong at debugging complex systems, identifying bottlenecks, and making architectures more reliable and efficient.
Experience
Application Developer
Aug 2024 — Present · Chicago, IL, US
Led backend development for the Uynite social platform, supporting over 100k+ installs across mobile and web.Built MuleSoft integration flows connecting AWS services, payment gateways, and email services for centralized service orchestration.Designed and built backend systems as a set of microservices using Java, Spring Boot, Kafka, and MongoDB.Implemented core features like user follow systems, OTP-based authentication, real-time notifications, content moderation tools, and story maps.Integrated Python-based ML models and AWS Rekognition for automated content screening and moderation workflows.Deployed and managed services on AWS (S3, CloudFront, EC2), improved performance with Redis caching, and ensured scalability using Docker-based deployments.Collaborated closely with frontend and mobile teams to ship features, debug production issues, and drive backend reliability and observability.
Education
Indian Institute of Technology, Madras
Internship, Electronics and Communications Engineering
Western Illinois University
Master of Science - MS, Computer Science
National Institute Of Technology Sikkim
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
2016 — 2020
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