About Me
Hey! I'm Aniketh Bharadwaj. I'm a Software Engineer focused on Systems, Test, and Automation Engineering.
I graduated with a Bachelor of Science in Electrical Engineering from Texas A&M University and am currently pursuing a Master of Science in Computer Science at Georgia Tech, specializing in Artificial Intelligence.
I'm passionate about System and Process automation, CI/CD pipelines, and increasing cost savings and efficiency through Software Engineering.
I currently work as a Software Test Engineer at Honeywell, focusing on automating test processes and developing robust testing frameworks to ensure product quality and reliability. Previously, I interned at Tesla and Honeywell, where I contributed to various projects involving real-time monitoring dashboards, automation scripts, and modernizing legacy systems.
You can find my resume here, and feel free to reach out via email or LinkedIn!
Experience
Honeywell
Software Engineer I
February 2025 - Present
Led automation initiatives and deployed FPGA drivers in C#/.NET, streamlining cross-department systems and driving $45K+ annual savings while accelerating hardware–software integration.
C#.NETFPGAAutomationSoftware Engineering Intern III
June 2024 - August 2024
Engineered and integrated a C# application for IVI-compatible instruments, reducing test station qualification time by 25% while ensuring backwards compatibility and enabling modular CI/CD maintenance.
C#IVICI/CDInstrumentationSoftware Engineering Intern II
June 2023 - August 2023
Developed and modernized a Temperature Chamber interface by converting legacy Visual Basic code to a streamlined C#/.NET solution, delivering cross-functional accessibility and improved code quality through a custom installer and QA plan.
C#Visual BasicQAInstallerTesla
Software Engineering Intern
October 2022 - January 2023
Designed and deployed real-time monitoring dashboards and automation scripts using Python, InfluxDB, and Grafana, streamlining energy storage test station operations, enabling cross-division scalability, and integrating live alerts via Microsoft Teams.
PythonInfluxDBGrafanaAutomation
Projects
Crop D.O.C
Developed Crop D.O.C., a full-stack mobile application using React Native, Firebase, and Flask that enables farmers to upload crop images and receive instant AI-based disease diagnoses. The model achieved a 95% accuracy rate, providing reliable insights for real-world agricultural use. Integrated Firebase Storage and Firestore to securely manage user-submitted images, custom crop names, and geolocation metadata, ensuring both scalability and data integrity.
Contact
Feel free to reach out to me via email or connect with me on LinkedIn!