Lokhesh Ujhoodha
Product And AI at Kurrent
Luxembourg
Summary
🤩
Rockstar🎓
Top SchoolLokhesh Ujhoodha is a pragmatic software engineer and product-focused AI practitioner with 11 years of experience building backend systems, operational support frameworks, and data platforms from Mauritius to Luxembourg. Currently driving Product and AI initiatives at Kurrent, he combines hands-on backend development (notably Python integrations for MindsDB and EventStoreDB) with a proven track record running engineering-aligned technical support that sustained >99.5% SLA performance. He has deep experience in event stores, test automation, distributed systems and big data stacks (Hadoop, Kafka, Elasticsearch), and has shipped production fixes and new database handlers in prominent open-source projects. Comfortable both leading teams—having trained multiple junior engineers—and diving into low-level troubleshooting (filesystems, kernels, Kubernetes), he brings a rare blend of customer-facing support rigor and software craftsmanship.
11 years of coding experience
10 years of employment as a software developer
BSc (Hons) Computer Science, BSc (Hons) Computer Science at University of Mauritius
English, French, Hindi, Luxembourgish
Github Skills (22)
eventstore10
python10
testing10
nunit10
event-sourcing10
dotnet-core10
csharp10
data-integration10
sql-database10
http-api9
authentication9
dotnet9
apidoc9
user-authentication9
net9
Programming languages (9)
Github contributions (5)
kurrent-io/EventStore
Apr 2018 - Aug 2022
EventStoreDB, the event-native database. Designed for Event Sourcing, Event-Driven, and Microservices architectures
Role in this project:
Backend Developer & QA Engineer / Test Automation Engineer
Backend Developer & QA Engineer / Test Automation EngineerContributions:37 reviews, 53 commits, 29 PRs in 4 years 4 months
Contributions summary:Lokhesh primarily contributed to the event store project by writing tests and fixing build errors. They created a new NUnit test to validate transaction log chunk corruption scenarios. Furthermore, the user addressed errors in test code and implemented new HTTP routes for the UI. These changes indicate a focus on improving code quality and enhancing the testing infrastructure of the event store system.
eventstoreevent-sourcingcqrsdatabasestream
mindsdb/mindsdb
Apr 2023 - Apr 2023
AI's query engine - Platform for building AI that can learn and answer questions over large scale federated data.
Role in this project:Back-end Developer
Back-end DeveloperContributions:4 reviews, 1 PR, 6 comments in 7 days
Contributions summary:Lokhesh primarily contributed to the development of a new database handler for EventStoreDB, which involved implementing functionalities for querying, retrieving tables, and retrieving column information. They added support for secure connections and authentication, improving the robustness and security of the integration. Furthermore, the user added a `native_query` function and implemented the `get_columns` function, indicating a focus on expanding the database handler's capabilities. The code changes indicate that the user developed the database handler in Python using the `requests` library.
localaimachine-learning-databasesolacesinglestoreexplainable-ml
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.