HELLO, I'M
Nikhil Juluri
Master’s student in Computer Science at UIC with experience building full stack enterprise applications and AI-enabled platforms. Skilled in Java, Spring Boot, React, Python, FastAPI, AWS, Azure, GCP, and GenAI tools like LangChain, LlamaIndex, RAG, and vector databases. I enjoy designing scalable systems that connect clean user experiences with robust backend and AI workflows.
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Years Experience
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Projects Completed
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Lines of Code
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Technologies Mastered
About Me
I'm a Computer Science graduate student at the University of Illinois Chicago, focused on building scalable Full Stack and AI-powered applications. My experience spans enterprise software development, backend systems, cloud deployment, and GenAI integrations across financial and research domains.
I work with technologies such as Java, Spring Boot, React, TypeScript, Python, FastAPI, Node.js, Express.js, PostgreSQL, MongoDB, Docker, Kubernetes, AWS, Azure, GCP, and CI/CD pipelines. I also build AI-enabled systems using LangChain, LlamaIndex, RAG, OpenAI API, Claude API, vector embeddings, FAISS, Pinecone, Chroma DB, Hugging Face, and PyTorch.
Previously, I worked at Deloitte on full stack financial applications for clients including T. Rowe Price and Edward Jones. At UIC, I have worked on AI-driven research platforms that combine software engineering, data workflows, and machine learning to help users search, analyze, and interact with complex information more effectively.
I'm looking for opportunities in Software Engineering, Full Stack Development, AI Engineering, and Full Stack AI Engineer roles where I can build reliable, scalable, and intelligent products.
Featured Projects
Showcasing advanced capabilities in GenAI, Large Language Models, and MLOps infrastructure.
Lazarus – Clinical AI Platform for Drug Repurposing
- •Architected a full-stack clinical AI platform that transforms failed drug assets into ranked repurposing hypotheses using a FastAPI + React/Vite control plane, PostgreSQL operational ledger, and Neo4j biomedical knowledge graph.
- •Built a typed 9-agent LLM orchestration DAG with 14 persisted reasoning steps per run, generating auditable outputs across hypothesis generation, skeptical review, evidence curation, trial strategy, effort estimation, and impact scoring.
- •Engineered real-time WebSocket streaming with polling fallback, enabling operators to monitor live agent traces, confidence scores, human-review escalations, portfolio rankings, and executive-ready PDF blueprint generation.
TrustLayer – Trust-Aware RAG Research Assistant
- •Built a trust-aware research assistant for local research-paper corpora by engineering an end-to-end RAG pipeline that indexes 5,000+ evidence chunks with Chroma vector search.
- •Improved answer reliability by implementing hybrid and corrective retrieval, combining dense embeddings with BM25 sparse search and cross-encoder reranking.
- •Increased transparency and reduced unsupported responses by 40% through verification-based abstention and an interactive dashboard for evidence visualization.
BugOrbit – Graph-Powered Incident Intelligence
- •Designed and built a graph-powered incident intelligence platform that transforms raw production telemetry into structured incidents and root-cause analysis.
- •Engineered a FastAPI and Neo4j pipeline to normalize noisy observability payloads and persist service dependencies as a live graph with <200 ms ingestion latency.
- •Developed an interactive React dashboard for live incident monitoring and dependency-graph exploration, reducing mean investigation time by 30%.
GraphRAG for Multi-Hop Question Answering
- •Built an end-to-end GraphRAG system for multi-hop QA, indexing 10,000 examples into 263,113 text chunks with dense retrieval and hybrid graph construction.
- •Designed a hybrid graph-retrieval pipeline with query-aware GraphSAGE and PCST-based evidence selection to improve multi-document reasoning.
- •Achieved significant performance gains over dense baselines, outperforming in downstream answer quality across evaluation sets.
PulseGrid (Kairos) – Real-Time Disaster Response Optimization
- •Designed a real-time graph-based decision-making system on Neo4j for resource dispatch and routing during disasters, facilitating sub-100ms updates.
- •Implemented multi-step routing using Priority Queues, Dijkstra’s, Yen’s K-shortest path, and Gale-Shapley algorithms for optimal responder matching.
- •Decreased responder deployment time by 45-50% while providing real-time route animations and ETA tracking via sub-1 second instructions.
High-Performance LLM Inference Framework
- •Built a high-performance LLM inference framework improving token generation throughput by 30-45% and reducing latency by 25% through optimized dynamic batching.
- •Designed benchmarking pipelines to analyze latency distribution (p50/p95), throughput, and GPU memory utilization across multiple model configurations.
- •Enabled systematic performance tuning and identification of inference bottlenecks under concurrent workloads using vLLM and CUDA.
Hackathon Achievements
Recognized at major hackathons for building advanced AI platforms and clinical R&D systems.
Microsoft HackWithChicago Finalist
Finalist at the Microsoft HackWithChicago hackathon for building BugOrbit, a graph-powered incident intelligence platform.
WildHacks (Northwestern University) Top 25
Selected as one of the top 25 projects at WildHacks by Northwestern University for PulseGrid, a real-time disaster response optimization system.
HackPrinceton Spring 2026 Sponsor-Track Runner-Up
Runner-up in the sponsor track at HackPrinceton Spring 2026 for Lazarus, an autonomous clinical R&D swarm.
My Experience
My professional journey in software and AI development.
Software Engineer
University of Illinois Chicago
Software Engineer II
Deloitte
Software Engineer I
Deloitte
My Education
University of Illinois Chicago
Master of Science in Computer Science
My Skills
Technical proficiency across various domains.
Programming & Data
Machine Learning
GenAI & NLP
Systems & MLOps
Certifications & Awards
Get In Touch
Let's work together and create something extraordinary.