Medha K.

About Medha K.

I am a Backend Engineer at Goldman Sachs building high-scale distributed systems and data infrastructure. I hold a Master’s degree in Computer Science from the University of Utah (2024), where I focused on advanced algorithms, distributed systems, and database internals.In industry, I design and develop production-grade backend systems in Java and C++, working on high-throughput messaging platforms, financial data systems, and streaming architectures. I am particularly passionate about algorithms, storage engines, indexing structures (B-Trees, LSM trees), and performance optimization. I enjoy understanding systems from first principles — how data flows, how memory is managed, and how latency can be reduced.Beyond traditional backend engineering, I actively explore AI-integrated systems and LLM-powered applications. I have built retrieval-augmented generation (RAG) pipelines, experimented with LangChain/LangGraph agent workflows, and integrated modern AI APIs to enhance backend intelligence and automation.Technically, I work across:• Java & C++ backend systems• Distributed messaging (Kafka-style architectures)• Databases & data modeling• Cloud-native systems (Docker, Kubernetes, Azure/AWS)• AI-assisted backend workflowsI am especially interested in:• Distributed systems engineering• Performance-critical C++ systems• AI + backend systems convergence• Storage & database infrastructureI’m always excited to work on challenging infrastructure problems at scale.

Experience

1. Associate Software Engineer

   Goldman Sachs

   Aug 2024 — Present · Salt Lake City, UT, US

   Backend engineer contributing to high-throughput, data-intensive platforms in a regulated financial environment. Focused on building reliable, scalable services for transaction processing, data aggregation, and reporting systems.Key Contributions:* Designed and implemented a high-throughput Java Spring Boot service to process and route millions of messages daily across distributed messaging systems (Kafka and enterprise messaging platforms), deployed on Kubernetes.* Delivered a configurable aggregation framework for financial positions and balances, enabling flexible grouping logic and ensuring time-aware data accuracy across streaming and analytical data stores.* Built streaming data pipelines using Apache Kafka to consolidate data from multiple legacy sources into centralized storage, improving reporting efficiency and data accessibility.* Explored LLM-enabled backend workflows by prototyping retrieval-augmented and prompt-driven services using modern AI APIs, focusing on secure integration patterns and system design considerations for production environments.* Developed a high-availability feed generation service with intelligent failover mechanisms, improving processing performance by 30%+ and increasing system resilience.* Contributed to reconciliation and audit reporting workflows by modernizing legacy logic into maintainable backend services, reducing operational dependency and long-term infrastructure costs.

Education

• Poornaprajna College, Udupi - 576102

  Pre university college, Computer Science

  2014 — 2016

• University of Utah

  Master of Science - MS, Computer Science

• JSS SCIENCE AND TECHNOLOGY UNIVERSITY

  Bachelor of Engineering - BE, Computer Science and Engineering

  2016 — 2020