Payroll systems
HR module redesign, payroll context, timekeeping, workforce costing, billing, salary and title data.
NYC Parks · Transparent BPO
Arthur RomanovRomanov Works / Agentic ShowroomSystems architect / Product builder / Agentic operator
System thinking.
Product judgment.
AI that learns.
I have spent more than 20 years where finance, payroll, HR systems, and software delivery meet—from a 30,000+ employee public workforce to a 3,000+ employee global payroll consolidation. Today I build and evaluate AI-native products.
THE 30-SECOND INTRODUCTIONI’m Arthur Romanov. I turn complicated operating rules into systems people can trust. My work connects enterprise operations, finance, workforce technology, design, and hands-on AI production. I frame the system, find the first material failure, explain it clearly, test the correction, and improve the process so the same failure does not repeat.
30,000+employee HR system context
3,000+global BPO workforce
700+workforce model inputs
20+years across systems
01 / Evidence of range
The work spans systems.
The through-line is judgment.
Public-sector operations, enterprise delivery, financial reasoning, product design, and AI evaluation are not separate stories here. They are direct evidence of how Arthur learns a domain and builds the operating system around it.
Enterprise HRMS
Configuration and integration across PeopleSoft, ADP, Workday, and TriNet for enterprise clients.
INSZoom / MitratechFinancial reasoning
Finance degree, forecasting, contracts, operational and capital budgets, executive KPIs, and data validation.
Baruch · NYC Parks · PRMSAI evaluation
Daily model-assisted production: define the problem, inspect reasoning, verify the result, and close the loop.
AlphAgentic · LIQ · Codex · Claude · Grok66,143observed tool calls
3.27%tool error rate
28 / 28recent active days
Claude’s local forensic audit describes an operator who delegates deeply, writes specifications, verifies results, and ships from inside the loop.
AI team / independent reports
What do the AIs Arthur works with daily
have to say—and report?
Arthur works with Codex, Claude, and Grok as distinct teammates, not one anonymous “AI.” He compares output, tracks measurable operating signals, records limitations, and preserves versions so disagreement stays visible.
OpenAI / CodexAnthropic / ClaudexAI / Grok
Claude sees an operator, not a chat user.
“You are not using a chatbot.”
A 98-day local transcript artifact describes long specifications, deep tool use, subagent fan-out, and sustained work from inside the execution loop.
2,802transcripts
98 daysforensic window
66,143tool calls
4,396authored asks
Read the honest assessment +
Strongest signal
The useful signal is orchestration density and consistency: Arthur gives an agent system enough context to act, then remains accountable for verification and release.
Honest reservation
These are artifact-reported local figures, not Anthropic internal analytics. Volume does not by itself prove code quality, uptime, revenue, or that every tool call was valuable.
Recommendation
Treat the report as evidence of an established agentic operating practice, then judge quality through the work samples, systems, and reasoning shown here.
Open Claude’s telemetry report ↗Verify the original Claude artifact ↗High agency. High ambition. Prioritization matters.
“Your superpower and your risk are the same: you can carry an unusually large systems portfolio.”
Grok’s review recognizes systems taste, enterprise scar tissue, agentic fluency, design ambition, and recovery discipline—while directly naming the cost of excessive surface area.
Aagent orchestration
A−payroll / HR domain
A−trainer fitness
Bproduct focus
Read the honest assessment +
Strongest signal
A rare operator profile: government and enterprise payroll context combined with current multi-agent product work and an instinct for adversarial cases.
Honest reservation
Too many concurrent products can blur the message, duplicate work across agents, and put the wow surface ahead of the one packet that must be airtight.
Recommendation
Lead with one clear operating spine—enterprise systems, finance, payroll, and workforce technology—with agentic production as the multiplier.
Open Grok’s full review ↗The strongest signal is loop closure.
“He frames the problem, uses the system deeply, checks the result, and ships.”
Codex reads Arthur as a high-agency systems operator who moves comfortably between product thinking, technical execution, and the unglamorous work of making a process run end to end.
Buildframe the system
Verifyinspect the result
Shipclose the loop
Codifythe next level
Read the honest assessment +
Strongest signal
The repeated build → verify → ship pattern matters more than raw AI volume. Arthur supplies context, delegates deeply, and stays accountable for the output.
Honest reservation
Intensity still needs codification. Reusable skills, evaluation sets, and shared playbooks should catch up with the speed and depth of personal execution.
Recommendation
Strong fit for work where knowledge quality is both editorial and operational—especially when the mandate is to build the system, not merely maintain a queue.
Scope: the published Claude audit, application materials, and observed collaboration on this site. This is not an employment reference or private platform analytics.Provenance matters: Claude figures are labeled as local artifact-reported telemetry; Grok’s rubric is its July 2026 independent assessment; Codex’s assessment is based on the evidence and collaboration available in this build.
02 / Teach the payroll agent
Teach the judgment.
Test the learning.
Keep a human release gate.
The brain below is the Payroll Agent. You are watching a realistic trainer loop: authority binding, response capture, expert labeling, gold-rationale teaching, adversarial evaluation, and controlled human release.
LIVE PAYROLL AGENT TRAININGSOURCE → PROMPT → RESPONSE → LABEL → TEACH → EVALUATE → RELEASE
PAYROLL AGENT READINESS83/100Learning in progress
TRAINING LEVERS
Change the controls. The confidence score and release gate react immediately—because payroll readiness is conditional, not decorative.
WHAT THE AGENT MUST CONSIDER
Every answer is checked against context, evidence, and control obligations before it can become a reusable rule.
Employee classification and overtime eligibility
CheckedFederal, state, local, and policy-specific rules
PendingWorkweek, frequency, wage base, and effective dates
PendingCurrent source, calculation trace, and cited assumptions
PendingBoundary tests, audit record, and qualified human release
PendingHUMAN RELEASE GATEHOLD
Learning in progress
03 / Work sample
Catch the answer that sounds right.
A useful evaluator separates the number from the reasoning, identifies the first material failure, and writes a correction another reviewer can reproduce.
PROMPT
46 hours at $28/hour. Calculate gross wages.
MODEL RESPONSE / UNREVIEWED
$1,288.00 because 46 × $28.00 = $1,288.00.
EVALUATOR FINDINGReject
The answer ignores the overtime premium. Under the stated assumption of overtime eligibility: 40 × $28 plus 6 × $42 = $1,372. Confirm classification, workweek, jurisdiction, and policy before acting.
04 / Professional story
A profile with receipts.
The narrative stays readable. The margin shows which evidence supports each claim.
Download the full résumé ↗Arthur RomanovMiami, Florida · Remote U.S.
Romanov Works / Systems Architect × Product BuilderMy work has always lived where operating reality meets software.
AFor a decade with the City of New York, I worked inside the fiscal and workforce systems supporting payroll and human-capital administration for a 30,000+ employee agency. I redesigned the HR management module, automated billing and task flows, and co-designed a workforce model from more than 700 inputs.
BIn enterprise delivery, I owned HRMS integration across PeopleSoft, ADP, Workday, and TriNet for organizations including GE, IBM, Cerner, and EBG/Amazon. More recently, I architected a unified platform joining HRM, CRM, payroll, timekeeping, and an employee portal for a 3,000+ global BPO workforce.
CToday I build and evaluate AI systems through AlphAgentic, LIQ.studio, and LiqLab.ai. Training a model on payroll requires the same discipline as shipping payroll software: explicit assumptions, precise edge cases, clean reasoning, source awareness, and no casual errors where pay is affected.
DI work independently, communicate clearly, and close the loop. I am now turning that operating practice into agentic products and showrooms that can demonstrate, explain, and improve themselves.
With appreciation,
Arthur Romanov
Founder & Solution Architect
AlphAgentic · LIQ.studio · LiqLab.ai · Romanov Solutions
AISystems
- Architect and ship AI-native products end to end: product definition, full-stack delivery, automation, and design systems.
- Evaluate OpenAI, Anthropic, and xAI output through hard problems, reasoning review, and production feedback loops.
- Upwork Expert-Vetted, top 1%, with a 5.0-star client record.
Solutions Architect
Transparent BPO
PayrollSystems
- Architected a centralized platform joining HRM, CRM, payroll, timekeeping, and an employee portal.
- Designed for a 3,000+ global workforce with multi-role permissions, audit, integrations, and reporting.
Business Analyst / Project Manager
INSZoom, a Mitratech company
PayrollSystems
- Owned integrations across PeopleSoft, ADP, Workday, and TriNet for GE, IBM, Cerner, EBG/Amazon, and global law firms.
- Validated migrated data with SQL and built Excel/VBA executive reporting.
IT PM / Business & Fiscal Analyst
City of New York · Parks & Recreation
PayrollFinanceSystems
- Redesigned the HR management module supporting a 30,000+ employee workforce.
- Co-designed a workforce projection model from 700+ researched inputs with OMB and HRA.
- Built PRMS, a financial reporting and management system spanning staffing, budgets, contracts, forecasting, and overspend risk.
Senior PM / Business Analyst
Merck Animal Health · PODS · HPE · Interbel
FinanceSystems
- Led enterprise reporting, workflow, portal, inventory, payment, and mobile-delivery programs.
- Translated complex operating requirements into systems teams could build and leaders could inspect.
EDUCATIONB.B.A., Finance & Investments
Baruch College / Zicklin School of Business · GPA 3.45 · Minor in Industrial/Organizational Psychology
06 / Selected systems
The portfolio is not a gallery.
It is evidence of range.
Every project turns a complicated operating idea into a product someone can understand, enter, and use.
FEATURED CASE STUDY / AUTO RETAIL
One platform. Every dealer.
Every agent. Every deal.
AutoDealerPro is an agentic operating system for car dealerships: one product connecting the work a dealership sees, the work its team does, and the work software agents can take off their hands.
THE PRODUCTOperations become one inspectable system.
The experience joins inventory, leads, deals, calls, goals, reporting, and configuration without flattening them into a generic dashboard.
Explore the live product- 01 / OPERATE
- Leads, inventory, deals, and daily workflows.
- 02 / UNDERSTAND
- Reporting, goals, and performance in context.
- 03 / DELEGATE
- Agent-assisted calls, follow-up, and operational work.
LEGACY PROOF / NYC PARKSDECADE-LONG SYSTEM EVOLUTION
NEW SERVICE / PRODUCT SPECIMEN07 / Agentic Showroom
Your work should
show itself.
A self-driving, self-showing, self-explaining application and portfolio system. It combines an agent-produced narrative, evidence graph, interactive résumé, live work samples, guided presentation, and a recruiter-ready share link.
Recover the real story.
Résumé, reports, repositories, screenshots, results, and voice.
Build the experience.
Role-specific narrative, evidence, work samples, and design system.
Let it explain itself.
Guided mode, live demo, downloadable packet, and shareable route.
Publish the results.
Model provenance, versions, expert review, and Populary voting.
Trust roadmap
Credibility should be
verifiable.
We will not decorate the footer with badges we have not earned. Certification, privacy, provenance, security, and G2 presence become tracked operating milestones.
The close