Bharat Patel
Head Of Engineering at SECURITI.ai
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolBharat Patel is an experienced software engineering leader with 12 years in the industry and over a decade building cloud-native SaaS platforms, currently serving as Head of Engineering in the San Francisco Bay Area. He combines hands-on expertise across backend languages (PHP, Python, Java), modern infrastructure (AWS, Docker, Rancher) and datastores (Oracle, MongoDB, Elasticsearch) to deliver large-scale distributed systems. His career spans leadership roles at SECURITI.ai, Symantec/Blue Coat and Qualys, where he architected high-throughput services handling billions of scan targets and introduced containerization and caching patterns across teams. A pragmatic, hands-on manager, he recruits and scales distributed engineering organizations while still contributing code—evidenced by meaningful contributions to the popular Machinery async task queue (SQS integrations and bug fixes). Known for bridging product, operations and security concerns, he thrives on turning complex requirements into reliable, maintainable services. He holds an MS in Computer Science and brings a blend of deep technical breadth and proven delivery at enterprise scale.
12 years of coding experience
13 years of employment as a software developer
BE Computer Science and Engineering, BE Computer Science and Engineering at Devi Ahilya VishwavidyalayaMS Computer Science, MS Computer Science at California State University, Fresno
Hindi, English
Github Skills (9)
rabbitmq10
golang10
task-queue10
message-passing10
go10
aws10
testing10
cd8
cicd8
Programming languages (6)
Github contributions (5)
RichardKnop/machinery
Sep 2018 - Dec 2019
Machinery is an asynchronous task queue/job queue based on distributed message passing.
Role in this project:
Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:12 commits, 9 PRs, 10 comments in 1 year 3 months
Contributions summary:Bharat primarily focused on enhancing the functionality and maintainability of the `machinery` project, an asynchronous task queue. Their contributions included implementing features related to SQS integration, such as supporting local SQS instances and enabling custom queue workers. They also addressed a bug related to receiving more messages than the system could consume. Furthermore, they exposed the SQS ReceiptHandle in task signatures.
jobmessage-passingmongodbmachinerymemcached
securitiai/machinery
Feb 2020 - Sep 2024
Contributions:7 releases, 10 reviews, 15 PRs in 4 years 8 months
machineryautomationmachine-learninglists
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