• Architect and maintain automated ATS candidate enrichment platform processing 5M+ profiles

quarterly using C#, TPL Dataflows, Azure Service Bus, PostgreSQL, and low-latency search services

• Built Kubernetes infrastructure for internal backend microservices with auto-scaling capabilities and

DNS-based routing

• Engineered entity mapping system using Pinecone vector database and GPT models to standardize

candidate data, improving accuracy for millions of profiles and enabling flexible model upgrades as new

LLMs are released

• Implemented master key database managing 1B+ entries with sub-200ms query performance handling

thousands of daily requests, unifying candidate profiles across multiple data sources

• Developed LLM-powered workflow feature delivering AI-scored candidate matches based on job

requirements, collaborating with runtime and frontend teams to define optimal data schemas

• Built E2E testing infrastructure and Azure DevOps CI/CD pipeline

• Created alert system with Slack integration, improving core-services incident response-time

• Saved $100K+ annually by migrating backend search index from Azure Cognitive Search to

PostgreSQL/Snowflake with strategic blob storage caching

• Helped implement automated data ingestion pipelines for multiple external providers, standardizing

diverse schemas into unified platform, processing 800M+ profiles a quarter

• Developed features for a high-fidelity, modular radar simulation software

• Created and managed API protocols

• Participated as a member of an agile team to progress the software product

• Designed and implemented GUI components for the end-user

• Analyzed problems in order to provide a development path forward for other developers

• Designed and implemented architecture within the software product, which improved the developing

environment for the team

• Developed features for ADTRAN Mosaic, a software-defined networking product

• Implemented unit testing, integration testing, and solution testing using pytest and testbeds

• Coordinated with team members as part of an Agile software development team

• Participated in pair programming, hot seat programming, stand-ups, and group code reviews

• Led demos on features and presented to the entire Fiber ART on behalf of the team

• Developed a test log analysis tool that parsed test logs, calculated inefficiencies, and visualized

issues within the testing process—reducing time in comprehension by up to 95%

• Performed data analysis and visualization on big data using Pandas, NumPy, and Plotly

• Developed a tool that parsed sensor data from hardware and displayed it in real-time