SYSTEM / 006
AI Hiring Assistant Platform
Modular AI pipeline with separated parsing, JD matching, and scoring layers. Async processing and queue-based ingestion for high-volume candidate flow.
Context
What this system is
Resume screening at volume creates bottlenecks when parsing, matching, and feedback are tightly coupled. Systems that treat the pipeline as a single monolith become hard to scale and difficult to iterate on (e.g. swapping models or changing scoring logic).
Ownership
What I was responsible for
This is a self-directed system — I owned the architecture, engineering, and product decisions end to end.
Architecture · Engineering · Product
The Problem
What made it necessary
Resume screening at volume creates bottlenecks when parsing, matching, and feedback are tightly coupled.
Architecture
How it's structured
- 01
Modular pipeline with clear service boundaries: parsing, JD matching, and scoring as independently deployable concerns.
- 02
Structured embeddings and deterministic prompt workflows so matching and feedback are auditable and reproducible.
- 03
Separation between ingestion (async, queue-backed) and read path (dashboard, real-time views) to avoid blocking under load.
Engineering Decisions
What shaped the system
- 01
Async processing and queue-based ingestion so submission spikes do not block system responsiveness.
- 02
Recruiter-facing layer designed for concurrent use and eventual consistency where appropriate.
- 03
Failure isolation so a failing component (e.g. one LLM call) does not take down the full pipeline.
Trade-offs
What was optimized for
Chose queue-based async over synchronous processing to favor throughput and resilience over lowest latency.
Kept matching and feedback logic in separate layers to allow model iteration without rewriting downstream consumers.
Outcome
Queue-based ingestion and service-boundary separation for horizontal scaling.
More Systems
Related systems
CXOps AI
Manage support intelligence, escalations, and SLA monitoring from one operations workspace.
ClinicAI
Run appointments, patient context, consultations, and clinic operations in one place.
Unified Analytics Platform
Turn scattered business data into clear KPI visibility and decision-ready insights.