
Knovel Protocol
Software Engineer · San Francisco Bay Area · Remote
Builds and ships recommendation, anomaly-detection and evaluation features on a blockchain data platform.
What the work was
- Implemented the similarity and recommendation layer behind content discovery and search, which decides what each user sees. It is built from written requirements, code-reviewed, and maintained after release.
- For the platform’s AI-enabled anomaly detection on blockchain transactions, wrote the detection code and defined the business logic and evaluation criteria: what counts as irregular, and which flags deserve an operator’s time.
- Built the post-release evaluation process the team measures output against. It decides which changes come next, and whether a data feature beat a simpler rule.
- Works between engineering and the people who run the platform, turning what an operator needs into a requirement the code can be checked against.
Growth
- Data AnalystMay 2024 – Sep 2024
- Software EngineerSep 2024 – Present
The path here
Before Knovel Protocol I did analytics at iHeartMedia and Divvy Homes. Rebuilding a reporting workflow on AWS at Divvy is what pulled me toward software.
That background is why I start with the domain model and the tests. Originally from Jamaica.
- Where
- San Francisco Bay Area · Remote
- Focus
- TypeScript · Python · Recommendations · Anomaly detection · Release evaluation