Full-Stack Engineer · AI/ML · DevOps

G.Hanumanth Reddy.

I build across the entire stack — from React frontends to AI pipelines, from database optimization to production monitoring. The engineer who traces problems through boundaries, not around them.

Get In Touch View Work
San Jose, CA 2.5+ Years Production Experience MS CS · 3.8 GPA
0% Error Reduction
0% Performance Gain
0% Latency Cut
0%+ Uptime Maintained
0+ Daily Requests
0+ Students Taught
01

About

The T-Shaped Engineer

I don't fit a single box. In 2.5+ years, I've debugged production crises, built RAG pipelines integrating LLMs with vector databases, optimized API performance by 40%, deployed containerized systems with Docker, created monitoring dashboards, and taught 150+ students.

When the frontend blames the backend, the backend blames the database, and the database blames the network — I can trace the actual problem. That's the value of breadth built through diverse real experience.

Frontend Backend Database AI/ML DevOps QA Monitoring
Production Troubleshooting
Root Cause Analysis
Cross-Layer Debugging
Performance Optimization
System Stabilization
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Immediate Contribution

Production code in JS/TS/Python/Java, CI/CD, monitoring, testing, debugging — no ramp-up needed.

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Proven Results, Not Promises

85% error reduction, 75% performance gain, 40% latency improvement — real production metrics.

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Fast Learner

Master's 3.8 GPA, Distinguished Student Award, mastered RAG/LLMs/vector DBs while delivering features.

02

Capabilities

01

Full-Stack Development

React, TypeScript, Node.js, Express, PostgreSQL, MongoDB. Complete applications from UI to database, deployed to production serving real users.

ReactTypeScriptNode.jsExpressPostgreSQLMongoDBReduxGraphQL
02

AI/ML Systems

RAG pipelines, vector databases (Pinecone, ChromaDB), LLM integration (GPT-4, Claude API), prompt engineering, AI agents for multi-step workflows.

RAGAgentic AILLMMLPineconeChromaDBGPT-4Claude APIPrompt Engineering
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DevOps & Infrastructure

Docker, CI/CD (Jenkins), AWS (EC2, S3, Lambda), Kubernetes basics, deployment automation, infrastructure as code. 99%+ uptime maintained.

DockerJenkinsAWSKubernetesCI/CDCloudflare
04

Monitoring & Observability

Prometheus, Grafana, Kibana, Splunk dashboards for system health. Alerting, distributed tracing, performance metrics, proactive issue detection.

PrometheusGrafanaKibanaSplunkDistributed Tracing
05

Production Troubleshooting

WebSocket crisis debugged (85% → <5% errors), API optimization (800ms → 200ms), distributed API latency cut 40%. Real fires, real pressure, real results.

Root Cause AnalysisPerformance TuningIncident ResponseOn-Call
06

Testing & QA Mindset

JUnit, Jest, Mockito, Postman. TDD, integration testing, accessibility testing (WCAG AAA). Quality embedded in engineering process.

JestJUnitPostmanTDDWCAG AAAMockito

Languages

JavaScript / TypeScript Python SQL Java Bash / Shell C++ Go
03

Experience

Sep 2025 — Present

AI Software Engineer

Mudra Labs · Houston, TX (Remote)
AI/ML · Distributed Systems

Architected and engineered end-to-end RAG pipelines, intelligent microservices, and automated alert triage systems, optimizing inference performance and ML data quality.

The Issue

Distributed microservice latency bottleneck impacting high-frequency AI inference endpoints.

The Fix

Profiled service chain, optimized async patterns, and implemented query-level caching — cutting response times by 40%.

  • Improved AI response accuracy by 40% over baseline outputs by architecting an end-to-end RAG pipeline utilizing Pinecone, ChromaDB, and multi-step context-aware prompt engineering.
  • Reduced manual alert review time by 70% by building an Intelligent Alert Handler system in Java and Python that automatically triages unstructured production alerts.
  • Cut API response latency by 40% for high-frequency LLM inference requests through service chain profiling, asynchronous pattern optimization, and query-level caching.
  • Sustained 99.9% uptime across unpredictable LLM workloads by developing resilient Node.js and Python backend microservices with adaptive rate limiting and circuit breakers.
  • Maintained high-quality ML training signals and caught data drift early by implementing rigorous Python validation scripts for embedding consistency and training data anomaly detection.
Jul 2025 — Sep 2025

Software Engineering Fellow (AI Research & Model Evaluation)

Handshake · San Francisco, CA (Remote)
AI Research · Orchestration

Engineered automated agent workflows and microservice scaling strategies for distributed model evaluation and process pipelines.

  • Engineered scalable automated workflows and multi-agent AI systems utilizing n8n and LLM orchestration to streamline technical processes and job application pipelines.
  • Optimized existing architectures into scalable microservices, ensuring high availability and seamless data flow across distributed backend systems.
May 2025 — Jul 2025

AI Engineering Intern

Socrates AI · San Mateo, CA (Remote)
ML Models · Analytics

Researched and implemented enterprise ML models for operational efficiency, and communicated value realization to product teams.

  • Prepared detailed technical presentations, dashboards, and progress reports summarizing AI model value realization and best practices for cross-functional product and engineering teams.
  • Accelerated the deployment of enterprise digital initiatives by actively participating in the research, design, and implementation of machine learning models tailored to improve operational efficiency.
Jul 2024 — May 2025

Software Engineer

University of North Texas · Denton, TX
Full-Stack · Web Accessibility

Developed and maintained critical university systems, resolving incidents, automating pipelines, and ensuring strict compliance with web accessibility standards.

  • Achieved WCAG AAA accessibility compliance across all key web interfaces by auditing and remediating color contrast, alt text, and screen reader compatibility.
  • Maintained 99%+ system uptime by deploying production updates via automated CI/CD pipelines and resolving connectivity incidents end-to-end.
  • Worked as a Graduate Teaching Assistant for Software & Intro to Big Data (2023-2024).
Jul 2022 — Aug 2023

Software Engineer

KLOG Solutions · Hyd, India
Full-Stack · Real-Time Systems

Shipped a full-stack shipment tracking platform from the ground up, optimized database performance, and resolved critical live WebSocket incidents under high load.

The Crisis

Critical production WebSocket outage (85% error rate, 200+ users affected).

The Fix

Traced reconnection storms under load, implemented connection pooling, retry logic, and heartbeat mechanism — error rate dropped below 5% within hours.

  • Reduced API response time by 75% (800ms to 200ms) on endpoints serving 5,000+ daily requests by refactoring query patterns and adding missing MySQL indexes.
  • Eliminated a critical production WebSocket outage (dropping error rates from 85% to <5% within hours) by tracing reconnection storms and implementing connection pooling and retry logic.
  • Shipped a full-stack shipment tracking platform from the ground up using a React/TypeScript frontend and Node.js backend to serve 200+ daily users.
04

Projects

Full-Stack

Full-Stack Blogging Platform

Hosted a scalable full-stack application on Cloudflare Workers, leveraging Prisma Accelerate for optimized connection pooling and Hono/PostgreSQL for the robust backend architecture. Built a responsive frontend using React and TypeScript, integrating JWT middleware to manage secure, role-based access control and user sessions.

ReactTypeScriptHonoPostgreSQLPrisma AccelerateCloudflare Workers
Machine Learning & Backend

Smart Parking System

Designed and implemented a machine learning-based prediction system using Express.js and MongoDB to optimize parking spot availability based on historical usage data.

Express.jsMongoDBPython MLPredictive Modeling
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Education

Master of Science

Computer Science

University of North Texas
May 2025 GPA: 3.8 / 4.0
Distinguished Student Award 2025
Software Engineering Distributed Systems Machine Learning Database Systems Computer Networks Algorithms Penetration Testing
Bachelor of Technology

Computer Science & Engineering

JNTU Hyderabad, India
Graduated June 2022

Certifications & Continuous Learning

◆ 100xDevs Full-Stack Development with DevOps
◆ Meta Front-End Development Specialization
◇ Currently learning: Advanced System Design, Kubernetes, Go, Advanced AI/ML
06

Contact

Let's Build Something Great.

Available immediately. Ready to contribute from day one. Whether it's full-stack development, AI systems, DevOps infrastructure, or production troubleshooting — I bring proven results, not promises.

Email hanugopavarapu@gmail.com
LinkedIn linkedin.com/in/ghanumanthreddy
GitHub github.com/ghanureddy