HR / Recruiting

Recruiting Management Platform Development & Maintenance (with AI Matching)

Development and maintenance of a recruiting management SaaS. Owns AI vector-search-based candidate matching and experience optimization for both companies and engineers.

Ongoing·Role: SES

Next.jsFastAPIPostgreSQLGCPLangChainPineconeFirebase

Challenge

Improving match accuracy between candidate skills and company requirements demands text-based matching.
Operational maintenance of a distributed setup combining GCP / Firebase / Pinecone.
Designed with PII protection (GDPR-equivalent) in mind.

Solution

Generated embeddings with LangChain, ran vector search on Pinecone, and layered on filters by skill / industry / salary.
Used Firebase Auth + GCP Cloud Run for serverless-leaning operation and cost optimization.
Defined masking / disclosure policies per PII field.

Technology Decisions

Why LangChain

Widely used as a common foundation for embedding and prompt management; library bug fixes and new features ship quickly.

Outcomes

Match Accuracy

+40% vs. random

Click-through-based A/B comparison

Search Filters

Multi-layered: skill × industry × salary

Vector search + structured filters combined

Serverless Mix

Mostly GCP Cloud Run + Firebase

Cost-optimized with reduced operational load

Team

1 of our engineers (SES)

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