# Mayank Goyal

> SWE 2 @ HPE(Aruba) | MS CS USC’23

Location: San Jose, California, United States
Profile: https://flows.cv/mayankgoyal

I’m a backend cloud engineer who enjoys turning complex distributed systems into reliable, scalable products that people can count on.

Over the past three years, I’ve built and operated production systems in Python and Java, working end-to-end on a greenfield platform from early design through launch and scale. Along the way, I’ve worked on Kafka-driven pipelines, tackled database bottlenecks, and managed services on Kubernetes, with a steady focus on performance, reliability, and clean system design.

I enjoy solving the challenges that come with designing and operating reliable systems at scale.

## Work Experience
### Software Engineer (Cloud) @ HPE Aruba Networking
Jan 2023 – Present | San Jose, CA
- Owned multiple end-to-end Python microservices and APIs, conducted low-level design reviews and delivered across both microservice and monolithic architectures.
- Led large-scale optimization of FCO’s Python microservices (ArangoDB, Kafka, Kubernetes), resolving bottlenecks to increase system scalability from 5K to 50K+ telemetry endpoints and cut infrastructure costs through efficient resource utilization.
- Drove production hardening through observability (Prometheus metrics, health probes, alerting), dedicated debug interfaces, and proactive monitoring—reducing customer-found defects.
- Prototyped AI-driven self-healing agents, demonstrating potential for autonomous monitoring and cost reduction.
- Designed and implemented a relay agent on embedded systems to relay telemetry between devices and the cloud and dispatch the results back to the edge device. 
- Increased system load capacity 10× by identifying scale bottlenecks and delivering the first scalable iteration of the core agent. Increase system scalability from 2K to 20K+ telemetry endpoints.

### Software Engineer Intern @ Hewlett Packard Enterprise
Jan 2023 – Jan 2023 | United States
- Designed and implemented a production-facing debugging aggregation API for a distributed microservices platform, enabling developers to retrieve comprehensive diagnostic data through a single REST endpoint.
- Developed orchestration logic in Python to automate production diagnostics, reducing manual debugging effort and accelerating incident resolution.
- Deployed and maintained containerized services using Docker and Kubernetes, contributing feature enhancements to improve service modularity and reliability.

### Graduate Teaching Assistant (Course Producer) @ University of Southern California
Jan 2022 – Jan 2023
Graduate Teaching Assistant (Course Producer) for CSCI 102 - Fundamentals of Computation

### Software Engineer Intern @ Hewlett Packard Enterprise
Jan 2022 – Jan 2022 | San Jose, CA
- Owned the design and implementation of automated testing infrastructure for a 7-service Python microservices platform, introducing CI-integrated validation where none previously existed.
- Built containerized test pipelines using Docker, Kubernetes, Jenkins, and Git, enabling consistent local and production test execution and improving deployment reliability.
- Developed comprehensive unit test suites with coverage reporting, enabling automated regression detection and reducing production defects.

### Software Engineer @ EA technologies
Jan 2020 – Jan 2021 | Noida, Uttar Pradesh, India
• Responsible for managing Machine Learning POC’s for clients including sales prediction, medical diagnosis etc.
• Designed and built a model on Diabetic Retinopathy with 86% accuracy.
• Created custom Convolutional Neural Networks and used transfer learning from prominent models.

### Research Intern @ Indraprastha Institute of Information Technology, Delhi
Jan 2020 – Jan 2020 | New Delhi Area, India
• Built a Brain Computer Interface for patients with Spinal Cord Injury (SCI).
• Analyzed Motor Imagery Data from EEG signals of SCI patients.
• Achieved objective of detecting and classifying movement intent using motor imagery.
• Developed a completely automated pre-processing pipeline for EEG signals.
• Studied brain networks and dynamic brain states.

### Intern @ MetaDesign Solutions
Jan 2019 – Jan 2019 | New Delhi Area, India
• Developed a POC in association with Medanta hospitals for diagnosis of medical images.
• Evaluated images of lungs for POC and worked on CheXpert dataset to improve accuracy.
• Designed a Deep Learning model using Convolutional Neural Networks and achieved an accuracy of 89%.


## Education
### Master of Science - MS in Computer Science
University of Southern California

### Bachelor of Technology in Information Technology
Manipal University Jaipur

### Delhi Public School - R. K. Puram


## Contact & Social
- LinkedIn: https://linkedin.com/in/mayank-goyal-58a04515b

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Source: https://flows.cv/mayankgoyal
JSON Resume: https://flows.cv/mayankgoyal/resume.json
Last updated: 2026-04-11