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GJ

New York, NY · IT Infrastructure · Networking · Automation

Systems engineer.
I design, troubleshoot, and integrate the complex systems everything else depends on.

From infrastructure and networks to software, automation, AI, and data — I work across the whole stack, because the interesting problems live where the layers meet.

  1. Engineering
  2. Infrastructure
  3. Networks
  4. Software
  5. Automation
  6. AI
  7. Data
View ProjectsExperienceResumeContact
Current
IT Systems & Infrastructure Manager
TAPPS Supermarkets
Degree
B.S. Industrial & Systems Engineering
Binghamton University
Automation
100+ hrs / month reclaimed
Home lab AI agents
ENGINEERINGINFRASTRUCTURENETWORKSSOFTWAREAUTOMATIONAIDATA
7 layers · 7 interfaces · one system

About

The through-line

My career runs along one axis — Engineering → Infrastructure → Networks → Software → Automation → AI → Data — with each layer feeding the next. What makes the work interesting is holding the whole system in view while being precise about any one layer.

  • 01

    Systems thinking, end to end

    Requirements, architecture, integration, verification — I treat a network, a database, or a drivetrain as one system with interfaces, failure modes, and constraints.

  • 02

    Root cause over symptom

    POS failures, network slowdowns, fabrication variance: the instinct is the same — measure, isolate, fix the mechanism, then write the procedure so it stays fixed.

  • 03

    Automation as leverage

    If a workflow recurs, it becomes a pipeline. My home lab — NAS, Docker, segmented access, and GPU inference driving AI agents — reclaims roughly 100+ hours a month.

  • 04

    Data closes the loop

    Cost analysis in SAP, benchmarked LLM inference, DOE on fiber diameter — every system I run produces data, and that data decides the next change.

Method

How I work

The same loop whether the system is a store network, a manufacturing process, or a home lab: measure → isolate → bound → automate → verify → learn.

  1. 01

    Measure before touching

    Instrument first: logs, baselines, uptime numbers, cost data. A system you can't measure is a system you can't fix.

  2. 02

    Find the root cause

    POS failures, network degradation, fabrication variance — isolate the mechanism, not the symptom. Then document it.

  3. 03

    Design the boundary

    Segregate what must not touch: dual networks, container isolation, blast-radius limits. Architecture is mostly drawing correct lines.

  4. 04

    Automate the repeatable

    If it recurs, it becomes a pipeline — backups, provisioning, reporting, research. Human attention goes to the exceptions.

  5. 05

    Verify, then validate

    Test the change, then test the system around the change. Restore drills, failover checks, edge cases — trust is earned.

  6. 06

    Close the loop with data

    Every system emits feedback — SAP costs, inference latency, fiber diameter. Feed it back in and iterate.

Experience

Increasing ownership, one layer deeper

From leading a drivetrain team, to keeping a residence hall online, to owning enterprise IT infrastructure — each step meant more of the system under my responsibility.

  1. IT Systems & Infrastructure Manager

    Aug 2024 – Present

    TAPPS Supermarkets · New York, NY

    Own the technical backbone of a multi-department retail operation: Windows database and POS infrastructure, a dual-network enterprise architecture built for data segregation, and the workflows that keep the business moving. Equal parts infrastructure engineering, reliability work, and business analytics.

    Infrastructure & Security

    • Windows database / POS infrastructure ownership
    • Dual-network enterprise architecture with data segregation
    • Security protocol development & firmware configuration
    • Ubiquiti networking across the enterprise

    Reliability & Optimization

    • POS root-cause failure analysis
    • Network infrastructure optimization
    • Dynamic workflow development

    Business & Data

    • Inventory optimization & procurement forecasting
    • SAP cost analysis & budget optimization
    • Cross-team requirements alignment

  2. Residential Computer Consultant

    Aug 2021 – May 2024

    Binghamton University — Information Technology Services · Binghamton, NY

    Front-line IT for a 200-student campus residence: device and network troubleshooting, uptime support, and the documentation practice that turns recurring incidents into better standard operating procedures.

    Support & Networking

    • Troubleshooting computing devices & networks
    • Network uptime support for a 200-student residence
    • Cross-team IT coordination

    Process & Documentation

    • System documentation & recurring issue analysis
    • Standard operating procedure improvement

  3. Drivetrain Lead

    Jul 2021 – Aug 2022

    Society of Automotive Engineers — BAJA · Binghamton, NY

    Led a five-person drivetrain team from design through production — part sourcing, BOM and cost-benefit discipline, and workflow adjustments when manufacturing timelines slipped. Systems engineering under real schedule and budget constraints.

    Design & Production

    • Drivetrain design and production
    • Task & project management for a five-person team

    Supply & Cost

    • Part sourcing with cost-benefit analysis
    • Bill of Materials (BOM) analysis

    Execution

    • Manufacturing delay analysis
    • Workflow adjustments to protect delivery

Technical showcase

A system I actually run

Personal infrastructure built to production standards — the same architecture, security, and reliability discipline I apply at work, applied to a system I own end-to-end.

Architecture — abstract

  1. L6Hardware

    Compute, GPU, redundant storage

    • I/O· Storage
    • compute· Containers
  2. L5Storage

    Redundant pools + automated backup

    • I/O· Hardware
    • reports· Automation
    • volumes· Containers
  3. L4Containers

    Docker isolation for every service

    • compute· Hardware
    • volumes· Storage
    • segmented access· Networking
    • runtime· AI
  4. L3Networking

    Segmented zones, minimal exposure

    • segmented access· Containers
  5. L2AI

    GPU-accelerated local LLM inference

    • runtime· Containers
    • inference· Automation
  6. L1Automation

    Agents for research & reporting

    • inference· AI
    • reports· Storage

Layers are abstract roles, not specific hosts.

Flows show logical data classes, not addresses.

Self-Hosted NAS, Virtualization & AI Agentic Infrastructure

Feb 2026 – Present · New York, NY

A home lab engineered like production: redundant storage, containerized services, segmented remote access, and GPU-accelerated local LLM inference driving automated research and reporting.

  • Redundant storage with automated backups — no single point of failure for personal data
  • Containerized service platform with isolated dependencies and repeatable deployment
  • Segmented remote access with a minimal external footprint
  • GPU-accelerated local LLM inference tuned across benchmarked models for latency and throughput
Read the full case study →

Projects

Systems I've built

Proof over claims — each project links to the architecture, the decisions, and the honest lessons.

All projects →

Skills

Disciplines, not buzzwords

Three overlapping practices — everything listed here is something I've actually used in the work described on this site.

01

9 skills

Systems Engineering

Treating requirements, integration, and verification as one discipline.

  • Requirements Derivation
  • Hardware/Software Integration
  • Systems Architecture
  • Root Cause Analysis
  • Verification & Validation
  • Risk Mitigation
  • Agile Frameworks
  • Lean Principles
  • Configuration Management

02

8 skills

Networking & Infrastructure

Designing and operating the layers everything else runs on.

  • Dual-Network Enterprise Architecture
  • Cisco Routers/Switches
  • Ubiquiti Networking
  • Firewall Configuration
  • Windows Server Domain Administration
  • Data Compartmentalization
  • Database Infrastructure
  • Linux Server Administration

03

11 skills

Software & Analytics

Building the tools and models that turn system data into decisions.

  • Python
  • MATLAB
  • SQL
  • Minitab
  • Arena Simulation
  • Microsoft Office
  • Next.js
  • React
  • TypeScript
  • Docker
  • Git

This site itself is part of the toolset — built with Next.js, React, TypeScript, and Tailwind CSS, running in Docker, versioned with Git.

Contact

Let's talk systems

Open to systems engineering, infrastructure, network engineering, and technical operations work. The fastest way to reach me is email.

Download ResumeBack to top

Engineering → Infrastructure → Networks → Software → Automation → AI → Data — one system, one career.