AI & Systems Engineer

Sri Harsha Vallabhaneni

MS CS @ CU Boulder (4.0) · RAG, FastAPI, Distributed Systems

RAG & GenAIFastAPI & DockerSystems Engineering

Experience

AI & systems engineering across enterprise and startups

AI Project Engineer (Capstone)

Cisco

2024 • San Jose, CA

  • Built enterprise incident triage system using LLMs and FastAPI
  • Reduced triage latency; production-grade log triage assistant for network diagnostics
  • Designed FastAPI microservices with MongoDB and Docker for scalable deployment

AI Intern

Empowered Margins

2024 • Remote

  • Built agentic AI pipelines for Excel data extraction and semantic header mapping
  • 85% reduction in manual processing through automated workflows
  • Multi-agent workflows for document processing

SDE 2

Darwinbox

2022 – 2024 • Hyderabad, India

  • Led RAG-based GenAI systems; reduced hallucinations by 95%
  • Built RAG-based AI chatbots used in production with high accuracy
  • Designed observability pipelines with real-time logs and dashboards

Skills

Tech stack and tools

Languages

PythonJavaScriptTypeScriptSQL

Backend & APIs

Node.jsFlaskFastAPIREST APIsMicroservices

GenAI / ML

LLMsRAGLangChainSentence TransformersPyTorchAgentic AI workflowsSemantic search

Data & Infra

MongoDBRedisKafkaVector Databases (Pinecone)DockerKubernetesGCP

Education

Academic foundation in Computer Science

MS Computer Science

University of Colorado Boulder

GPA: 4.0

Aug 2024 – May 2026

Key Coursework

Datacenter Scale ComputingNLPBig Data ArchitectureNeural Networks and Deep LearningData Mining

BE Electronics and Communication Engineering

BITS Pilani

Aug 2018 – May 2022

Key Coursework

Digital Image ProcessingOperating SystemsSoftware EngineeringIoTData Structures & AlgorithmsObject-Oriented Programming

About

I'm an AI and Systems Engineer (MS CS, CU Boulder, 4.0 GPA) focused on building reliable systems at the intersection of backend engineering and applied AI. My work spans enterprise-scale systems at Cisco and fast-moving AI teams, where I've built production-grade LLM systems, RAG pipelines, and agentic workflows.

I focus on systems that reduce ambiguity and deliver measurable impact: observability, scale, and exactly-once semantics.