AI Trainer tracks · Miami / Remote · $50–100/hr
Future-proof your career
Not a chatbot operator. A solutions architect who built payroll, HRMS, and workforce systems — now training models on the edge cases multinationals actually hit.
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Operator proof
You are not reviewing a resume filler.
Two honest channels: (1) a Claude Code forensic telemetry artifact — labeled as artifact, not re-audited here; (2) live GitHub org facts for αAgentic Solutions.
Enterprise spine
- NYC Parks — HR for 30,000+ · fiscal $15–100M · workforce model 700+ inputs
- Transparent BPO — unify HRM · CRM · Payroll · Timekeeping · portal (3,000+ global)
- INSZoom / Mitratech — PeopleSoft · ADP · Workday · TriNet
- Upwork Expert-Vetted top 1% · ships AI-native products under AlphAgentic
Reports
Full write-ups, not just hero numbers.
System Brain
Self-learning. Self-healing. Self-patching.
Multi-algorithm cortex: route, retrieve, reason, detect, heal, distill priors. Move the mouse — regions light with meaning. Open fullscreen for the live 3D topology.
After a core curriculum, human corrections become signals. Signals distill into versioned priors — inspectable, reversible, promote-only-when-measured.
Vertical · Payroll AI Trainer
Interactive payroll training flow
Hover each node. This is how models should be taught: policy → edge case → calc → exception → audit.
Gross build
Regular, OT, shift differentials, commissions, taxable benefits. Edge: mid-period rate change, retro pay, multi-rate jobs.
Vertical · Timekeeping
Time → pay integrity
Missing punches, OT thresholds, and work windows differ by country and CBA. Train the model on the chain, not a single formula.
Capture
Badge, app, roster import. Edge: dual clocks, timezone boundaries, remote vs site, offline sync collisions.
Multinational policy matrix
Local rules. Global employer.
Multinationals don’t run one payroll brain — they run many legal regimes. Hover a country chip; the matrix updates leave, OT, work windows, and unemployment notes (illustrative training content, not legal advice).
Training framing for AI evaluation · Transparent BPO-class multi-country ops experience · not a substitute for counsel
How I train models
Curriculum → edge cases → scored feedback
Core curriculum
Pay components, calendars, statutory vs voluntary deductions, tax residency basics, audit trails.
Country overlays
Leave accruals, OT thresholds, night/Sunday premiums, permitted work windows, termination pay patterns.
Adversarial cases
Mid-cycle transfers, dual employment, retro corrections, garnishment priority, misclassified contractor.
Score the reasoning
Not just the number — which statute path, which exception table, what would fail audit.
0Policy domains in matrix
0Flow nodes live
0Countries selectable
0Reports on file
Application packet
Ready for DataAnnotation assessment.
Interactive role kit (Payroll, Financial, Payments, Software), downloads, 24-project portfolio, and operator reports.
Arthur Romanov · arthur@liqlab.ai · 954.951.5911 · alphagentic.io