Software Engineer North Carolina

ADITYA CHITLANGIA

USA *******@****.*** github.com/adityachitlangia linkedin.com/in/aditya-chitlangia/ 919-***-**** Software Engineer with 4+ years of experience building scalable cloud infrastructure, data-intensive systems, and full-stack applications. EDUCATION

North Carolina State University, NC August 2023 - May 2025 Master of Science in Computer Science (CGPA 3.97/4.0) Coursework: Software Engineering, Object-Oriented Design, Cloud Computing, Data Structure and Algorithms, Computer Networks, Generative AI Vellore Institute of Technology, Chennai, India July 2016 - August 2020 Bachelor of Technology in Computer Science and Engineering (CGPA 8.62/10) Coursework: Data Structure and Algorithms, Database Management Systems, Machine Learning, Image Processing, Large-Scale Systems, Virtualization SKILLS

Programming Languages: Python, SQL, C++, TypeScript, JavaScript, Java, Shell Scripting, HTML, CSS Full-stack/ Cloud: FastAPI, Flask, Node.js, Kafka, Kubernetes, Redis, Microservices, React, Material-UI, Vite, AWS (S3, Lambda, Glue, DynamoDB) Databases/Data Engineering & Analysis: MySQL, MongoDB, Snowflake, Spark, ETL, DBT, Airflow, Power BI, Tableau DevOps & Tools: Jenkins, Spinnaker, CI/CD, Terraform, Docker, Chef, Grafana, Zabbix, Splunk, Jira, Linux, Agile, Git CS Fundamentals: Object-Oriented Programming, Design Patterns, Algorithms, Unit-testing, Debugging, Software Development Life Cycle, REST API WORK EXPERIENCE

Software Engineer Axil Health, North Carolina October 2024 - Present

• Designed 10+ HIPAA-compliant RESTful APIs using FastAPI securing 35,000+ patient records across 20+ clinics through JWT authentication, and role-based access control; achieved zero breaches with high system availability.

• Created responsive patient dashboard (React, TypeScript, Material-UI) with real-time Chart.js visualizations; slashed API latency 25% through Vite- optimized Axios calls, supporting 1,000+ concurrent users.

• Streamlined clinical analytics pipeline for 35,000+ patient records using Pandas/NumPy; implemented EWMA for anomaly detection, triggering alerts and cutting analysis time 60%.

• Built a KPI microservice delivering sub-200ms queries for 100+ clinical staff, lowering HR review time by 60% & enabling data-driven staffing decisions.

• Implemented modular ETL jobs in DBT & Airflow (Python/SQL) to refresh 17 pharmacy revenue feeds daily, accelerating pipeline runtime by 35% and uncovering $5K+/month in overlooked billing codes. Research Developer Guilluy Lab at NCSU, North Carolina January 2024 - August 2024

• Automated nucleus analysis in 10,000+ microscopy images by quantifying morphological features (OpenCV), transforming raw visual data into structured datasets, and reducing manual annotation effort by 55%.

• Constructed an end-to-end ETL pipeline (Pandas, SQL) to integrate fragmented datasets from 3 sources into a centralized data warehouse, enabling cross- comparative analytics and cutting data preparation time by 70%.

• Performed EDA to identify trends in cell behavior, delivering actionable insights on Power BI dashboards that boosted team productivity by 60%. Software Engineer Oracle July 2020 - July 2023

• Led AWS cloud migration leveraging Python and Terraform to migrate 2,300+ on-prem servers to AWS, enabling real-time ETL of 50+ TB/day healthcare data and reducing deployment time by 55%.

• Created Python tooling to integrate Zabbix alerts with Jira API, auto-generating incident tickets & reducing manual effort by 70%, and alert backlog by 40%.

• Optimized AWS S3 usage cost via lifecycle policies and deduplication, cutting storage costs by 65% and saving $100K+/year for an EHR analytics platform.

• Streamlined cloud provisioning for 50+ clients with Chef/OpenStack, accelerating environment setup by 40% through infrastructure-as-code practices.

• Managed Jenkins/Spinnaker pipelines for 50+ monthly CI/CD deployments, decreasing rollout failures by 25% by Splunk log analysis.

• Built monitoring systems (Grafana, Splunk, Zabbix) that mitigated 80% of production incidents and improved MTTR to 15 min during on-call rotations. Software Engineering Intern Oracle December 2019 - June 2020

• Automated database migrations with Python scripts, streamlining JDBC string updates and reducing manual effort from 700 to 60 hours per year.

• Migrated client’s on-prem infrastructure to scalable OpenStack environment using Chef for automated provisioning, cutting infrastructure costs by 25%. ACADEMIC PROJECTS

Job Application Tracking and Analysis Platform [Git]

• Built a full-stack Flask platform (Python, SQLAlchemy, Pydantic) to log and monitor 300+ job applications, automate interview tracking, and calculate success metrics; decreasing manual tracking by 80%.

• Enabled deadline alerts using (APScheduler/SMTP), implementing real-time querying & email notifications, eliminating missed deadlines by 80%. Real-time Predictive Resource Auto-Scaling System [Git]

• Architected a predictive autoscaler (Kubernetes + Facebook Prophet) to forecast CPU spikes 150s ahead; reduced SLO violations by 44% compared to default K8s HPA.

• Integrated Prometheus to scrape 10-second pod-level CPU metrics & streamed data over C++/Kafka, caching forecasts in Redis for sub-1ms access latency.

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