Kunal Saxena
Ashburn,VA
Summary
Senior in computer science and data science with expertise in developing production-grade AI systems and cloud-native backend infrastructure on AWS. Proficient in cybersecurity, fault injection, AI-assisted testing, and scalable distributed services. Research experience includes designing context state architectures for LLM systems and enterprise graph knowledge platforms. Focused on AI infrastructure, applied LLM systems, cloud security, and backend engineering roles.
Overview
2
2
years of professional experience
2
2
Certifications
Work History
Cybersecurity Engineering Intern
CVS Health
Hartford, CT
05.2025 - 08.2025
- Designed and implemented AI-assisted fault injection workflows within CI/CD pipelines, increasing AWS configuration test coverage by ~30%
- Built automated parameter exploration systems reducing manual security testing effort by ~40%
- Evaluated distributed cloud infrastructure configurations to identify security weaknesses and failure modes
- Improved resilience validation workflows for enterprise-scale AWS deployments
- Digital, Data & Analytics Technology
Software Engineer Intern
Valor Healthcare
Crystal City, VA
06.2024 - 08.2024
- Developed AWS-backed backend services supporting invoice processing systems handling thousands of monthly transactions
- Investigated and resolved production failures, reducing recurring runtime errors and operational escalations
- Improved system observability through structured logging and validation checks, accelerating debugging workflows
- Strengthened reliability of compliance-sensitive healthcare infrastructure
Software Engineer Intern
Volans Corporation
Ashburn, VA
06.2023 - 08.2023
- Built Java-based AWS APIs supporting an AI-driven predictive alerting platform for DHS CISA stakeholders
- Contributed to backend systems processing high-volume telemetry and event data for near-real-time alert generation
- Improved backend stability and scalability under burst traffic and distributed workload conditions
- Supported cloud infrastructure integration and performance optimization
Education
Bachelor of Science - Computer Science and Data Science
University of Pittsburgh
Pittsburgh, PA05-2026
Skills
- Python and Java
- C/C and SQL
- Bash scripting
- RAG and GraphRAG
- Embeddings and Neo4j
- LangChain and OpenAI API
- Context state architecture
- AWS and Terraform
- Docker and CI/CD
- FastAPI and REST APIs
- Distributed system design
- AI-assisted fault injection
- Chaos Toolkit
- Configuration validation
- Cloud security testing
Research
- LLM Systems Research – Context State Architecture, University of Pittsburgh
Research focused on designing structured context state architectures for LLM systems to improve inference determinism, scalability, and response relevance. Developed multi-layer state pipelines separating job-level, shared, and user-visible context, and applied findings to production-style RAG and AI infrastructure generation systems using Python, Neo4j, FastAPI, and OpenAI API.
Projects
- Terraform Generator / AI Architecture Assistant
LLM-driven system that converts high-level architecture specifications into validated Terraform infrastructure. Integrates ChaosToolkit to automatically generate and execute fault injection experiments, improving cloud configuration reliability and reproducibility. Built using Python, Terraform, AWS, and OpenAI API. - Wayfinder – Accessibility-Aware Routing Engine
Pedestrian routing engine using Valhalla and OpenStreetMap designed for accessibility-aware navigation and elevation-sensitive pathing. Implements a scalable FastAPI backend with asynchronous job pipelines for routing, elevation analysis, and tile generation. Built with Python, FastAPI, Valhalla, and Docker. - GraphRAG Documentation Intelligence System
Enterprise GraphRAG platform that ingests Jira issues, dependency graphs, and engineering artifacts into Neo4j knowledge graphs to enable multi-hop reasoning and context-aware retrieval. Combines semantic embeddings and graph traversal to accelerate root-cause analysis and engineering knowledge discovery. Built using Python, Neo4j, FastAPI, AWS, and OpenAI API.
Certification
- AWS Cloud Practitioner Certified License - August 2024
- OCAJP License - March 2023
Leadership Experience
- TEDxPitt — Speaker Coaching & Event Operations
- SOAR — Autonomous Rover Software
- Young Scholars Circle — SAT Math & Programming Instructor
Timeline
Cybersecurity Engineering Intern
CVS Health
05.2025 - 08.2025
Software Engineer Intern
Valor Healthcare
06.2024 - 08.2024
Software Engineer Intern
Volans Corporation
06.2023 - 08.2023
Bachelor of Science - Computer Science and Data Science
University of Pittsburgh