Xeurix

1. Challenge & Constraints

High CPU usage and database performance degradation when parsing high-volume resume files and executing semantic search queries across millions of jobs.

2. Architectural Solution

To solve these bottlenecks, the system was built using the following core patterns:

• Engineered a scalable Node/NestJS backend with PostgreSQL indexes and Redis-backed worker queues.
• Implemented semantic similarity search indexing over 10M+ job vacancies.
• Designed a dynamic PDF parser converting resume files to structured JSON vectors.

3. Measured Outcomes

• Reduced matching latency by 70%, helping job seekers secure interviews 3x faster.
• Outreach systems deliver over 100k automated applicant campaigns weekly.
• Match-scoring algorithms reduced manual filter tasks by 90%.