Case study 01 · Sanitized private system
Job Search Command Center
A privately operated system that turns inconsistent ATS feeds into a normalized, cost-aware application workflow with explainable recommendations.
System design, adapters, data model, evaluation contracts, dashboard, deployment, and operations
The problem
What needed to change
Job leads arrived from different applicant-tracking systems with inconsistent fields and duplicated lifecycle work. Generic keyword matching obscured seniority, location, compensation, and application-plausibility risks. Model calls also needed explicit cost controls.
I designed and built the ingestion adapters, normalized data model, evaluation contracts, application-state workflow, operational dashboard, scheduled pipeline, Telegram digest, private deployment, and test coverage.
System map
One request, traced end to end.
- 01ATS sourcesAshby · Greenhouse · Lever
- 02Adaptersretrieve · normalize · deduplicate
- 03SQLiteraw jobs · evaluations · lifecycle
- 04Evaluatorschema · scoring · cost telemetry
- 05Interfacesdashboard · Telegram digest
Key decisions
Designed for trust and operability.
Keep source quirks at the edge
Each ATS owns its retrieval and normalization logic. Downstream evaluation consumes one source-agnostic contract instead of accumulating vendor conditionals.
Put deterministic state around model output
Deduplication, eligibility, lifecycle transitions, and cost gates remain deterministic. LLM output is schema-validated and stored with model, latency, token, prompt-version, and cost telemetry.
Treat cost as a product constraint
Already-evaluated, applied, closed, incomplete, or implausible records are filtered before model use. The dashboard cannot trigger paid evaluation.
Design an operational surface, not a demo
The dashboard exposes recommendations, run health, service state, and application lifecycle while keeping ingestion and scheduler controls outside the UI.
Tradeoffs
What this design optimizes—and what it does not.
- SQLite favors operational simplicity over horizontal scale.
- A private network and shared token fit a single-user threat model; this is not multi-tenant authentication.
- Explicit workflow boundaries add code but reduce accidental spend and state corruption.
Verification
Private does not mean unverifiable.
- 89 tests plus 2 subtests pass in the private repository.
- Three independently implemented ATS integrations use a common normalized contract.
- Evaluation output is schema-constrained and recorded with per-run telemetry.
- The private service is monitored through health and administration views.
Interview walkthrough
Ask me to trace the system live.
I can provide a guided, sanitized walkthrough of the workflow, representative code, architecture, automated tests, failure modes, and the changes required at larger scale.