# Apaar B.

> simulations @doppel | ex-aws | aws dop

Location: New York, New York, United States
Profile: https://flows.cv/apaar

I’m a software engineer at Doppel in New York, where we’re building an AI-native social engineering defense platform.

My work focuses on designing scalable systems that monitor billions of domains, social media accounts, apps, and dark web forums, leveraging AI agents to proactively identify and neutralize digital threats. I enjoy operating at the intersection of infrastructure, security, and applied AI, and doing whatever it takes to build what our customers actually need. 

Previously, I worked at AWS and Capital One, where I built distributed systems at scale across cloud infrastructure and backend platforms.

I’m excited about the future of AI in security, and I’m very happy at Doppel. I am currently not exploring new opportunities.

## Work Experience
### Software Engineer @ Doppel
Jan 2026 – Present | New York, NY

### Software Engineer @ Amazon Web Services (AWS)
Jan 2024 – Jan 2026 | New York, NY
AWS ECR

### Software Engineer @ Capital One
Jan 2023 – Jan 2024 | Atlanta, Georgia, United States
•	Deployed a database migration from RDS PostgreSQL to Aurora Global PostgreSQL using AWS DMS resulting in a 3x increase in throughput and a seamless transition of data with minimal downtime.
•	Developed and productionized a dynamic QR code generator REST API in GoLang, incorporating feature-oriented programming; images are securely loaded to Amazon S3 & the component is deployed on AWS EC2, resulting in annual savings of 2 million sheets of paper and $700,000 in printing costs. 
•	Built a component to detect multiple or duplicate letters, alerting on-call engineers of potential production failures using AWS CloudWatch, Java, and AWS ECS, backed by MongoDB.
•	Spearheaded the design, development, testing, and deployment of a serverless Go API powered by AWS to retrieve current credit line increase data resulting in a 99% cost reduction compared to the prior API.

### Associate Software Engineer @ Philadelphia Phillies
Jan 2023 – Jan 2023 | Philadelphia, Pennsylvania, United States
• Developed Python web scrapers to extract data on prospective players from deprecated vendors.
• Utilized Google Cloud services to store and manage scraped data in secure and accessible buckets.
• Automated scraping process using GET and POST requests in Python with Apache Airflow to optimize efficiency and streamline data aggregation and integration into SQL-based databases with SQLAlchemy.

### MLE and SWE @ John Deere
Jan 2021 – Jan 2023 | Champaign, Illinois, United States
• Devised image processing algorithms to convert thousands of ground truth low-light images of planted seeds into high-quality images utilized for labeling training data via LabelMe.
• Constructed a state-of-the-art convolutional neural network using YOLOv4 to identify seed planting and predict crop yield based on critical factors such as seed orientation, trench depth, and soil composition.
• Created an end-to-end server infrastructure for seamless transmission of Deere's real-time sensor data.

### Research Assistant @ NASA - National Aeronautics and Space Administration
Jan 2018 – Jan 2021 | Greater San Diego Area
•	Implemented data science methods to track astronaut performance under testing conditions and recommended astronaut's fit for missions 
•	Built statistical models to test hypotheses of alternative fuel for space
•	Work was used in the 2020 NASA x SpaceX launch


## Education
### Master of Computer Science - MCS in Computer Science
University of Illinois Urbana-Champaign

### Bachelor of Science - BS in Computer Science
University of Illinois Urbana-Champaign


## Contact & Social
- LinkedIn: https://linkedin.com/in/apaarbh
- Portfolio: https://apaarbh.com

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Source: https://flows.cv/apaar
JSON Resume: https://flows.cv/apaar/resume.json
Last updated: 2026-04-13