JP Jorge A. Perez
Résumé

Senior Data Engineering Lead  ·  Applied AI

Jorge A. Perez

Engineer who turns business problems into shipped AI systems. Most recently replaced a daily two-person manual review with a vision-language model pipeline that inspects site imagery and routes findings into Jira, email, and SMS — roughly 1,000 person-hours a year returned to the business.

Eleven years across hands-on software and data engineering, customer-site deployment, and the translation between what operations needs and what engineering builds. MBA and BS Computer Engineering — fluent in both the technical design and the business case.

Get in touch LinkedIn

📍 Tampa, FL Open to conversations about applied AI and data platform work

11 Years in software, data & field engineering
~1,000 Person-hours a year returned by one AI pipeline
4 Issued U.S. patents as co-inventor
1.4B Rows in the production platform he built

About

Between the operation and the engineering

I spend my time where a business process meets the system that is supposed to carry it. Eleven years of that has been hands-on: writing the software, designing the data model, standing up the infrastructure — and then commissioning it at a customer site and training the people who have to live with it.

The work I care most about now is applied AI that survives contact with production: models that run on a schedule, evaluate against criteria someone actually agreed to, and take an action that closes a loop. Measurement comes with it — alert volume, escalation tiers, time to resolution — because that is how you know whether an automation is working or just running.

Selected impact

What that looks like in practice

AI against a real process

Built the vision-language model pipeline — scheduled perception, model evaluation, severity classification, and automated action into ticketing and alerting — that replaced two analysts spending two hours a day on manual review.

Forward deployed by background

Eleven years designing, commissioning, and supporting systems at customer sites, and acting as the technical voice to non-technical stakeholders and executives.

Prototype to production

Partners with R&D to move concepts out of proof-of-concept into field operation, then writes the runbooks, specifications, and training that make adoption stick.

Measurement built in

Defines the operational metrics — alert volume, escalation tiers, time to resolution, cache and query performance — that show whether an automation is actually working.

Experience

Where I've done it

Senior Data Engineering Lead

Aviro360 (formerly the ConGlobal technology group) · Odessa, FL

Nov 2025 — Present

  • Built agentic automation for the Network Operations Center: a vision-language model pipeline samples camera images from customer sites on a schedule, evaluates each against defined quality and fault criteria, classifies severity, and acts on the result — opening Jira tickets or dispatching email and SMS per configured escalation tier, with no human in the loop. Replaced a manual review that occupied two analysts for two hours every day.
  • Work across R&D, design, deployment, support, and data teams to find where automation returns the most operational value, then lead the work from concept through production.
  • Partner with R&D to move emerging concepts from prototype into field operation: design the training-data collection behind supervised computer vision models for license plate and container code recognition, match capture conditions to production inference, and validate model performance in the field.
  • Built the production data platform from scratch on PostgreSQL and AWS RDS Multi-AZ: 340 GB across 334 tables and 1.4 billion rows, sustaining 3.9 million transactions and 7.9 million row inserts per day at a 99.3% cache hit ratio and zero deadlocks.
  • Own the Network Operations Center and the metrics behind it — monitoring through Grafana and Loki, alert routing, escalation tiers, automated remediation, and root-cause follow-through — across an edge estate of about 20 customer sites on AWS EKS, Kafka, and Kinesis/MSK.
  • Manage and mentor a cross-functional team of seven across data engineering, IT, systems administration, and field operations, and own hiring end to end.
  • Report platform health, risk, and roadmap to technical and executive stakeholders, translating operational signal into business decisions.

Senior Data Engineer / Team Lead

ConGlobal · Odessa, FL

Jul 2023 — Nov 2025

  • Led data engineering and database architecture for large-scale, mission-critical operational systems, defining the data models and storage strategies behind real-time integrations, reporting, and analytics.
  • Partnered with analytics and BI teams to deliver data products and dashboards that business users actually adopted.
  • Served as technical lead for system integrations, translating business requirements into technical designs across internal and external systems.
  • Mentored engineers and DBAs and coordinated delivery with project management, QA, and business stakeholders against timeline and quality targets.

Senior Systems Integration Engineer / Team Lead

Communication Concepts Integration (acquired by ConGlobal, 2023) · Odessa, FL

Jan 2020 — Jul 2023

  • Primary technical point of contact for cross-functional teams and the customer-facing voice on project status, risk, and trade-offs — communicating complex technical detail to non-technical audiences.
  • Gathered requirements with project managers and business analysts, defined scope and deliverables, and owned the architecture that satisfied them.
  • Led development of integrations across applications, databases, and field devices using REST APIs, middleware, and related tooling.
  • Defined the integration standards and best practices adopted across the engineering organization.

Systems Integration Engineer

Communication Concepts Integration · Odessa, FL

Jan 2017 — Jan 2020

  • Planned, implemented, and commissioned software, hardware, and network infrastructure at customer sites, and developed cross-platform software in Java, C#, and C/C++ against PostgreSQL and MySQL.

Computer Engineer (Founding Engineer)

Communication Concepts Integration · Odessa, FL

Sep 2015 — Jan 2017

  • Founding engineer and one of the first technical hires at the startup, building the initial computer vision products with OpenCV and MATLAB and the engineering practices the team scaled on.

Patents

Issued U.S. patents, co-inventor

US 12,020,148 B1

Rail-yard automation systems

Issued Jun 25, 2024

Google Patents ↗

US 12,217,183 B2

Rail-yard automation systems

Issued Feb 4, 2025

Google Patents ↗

US 12,254,439 B2

Container-terminal automation systems

Issued Mar 18, 2025

Google Patents ↗

US 12,391,478 B2

Inventory / stacked shipping asset optimization

Issued Aug 19, 2025

Google Patents ↗

Education

Training

Skills

Toolkit

Applied AI

  • Vision-language models in production
  • Agentic automation patterns
  • Scheduled perception
  • Policy-based routing
  • Automated tool invocation
  • Computer vision (OpenCV, RTSP, GStreamer)
  • Training-data design & field validation
  • Edge inference on NVIDIA Jetson
  • Model deployment & monitoring

Solution design & delivery

  • Business process analysis
  • Proof-of-concept & prototyping
  • KPI definition
  • ROI measurement
  • Adoption enablement
  • Runbooks & user training
  • Agile (Scrum, Kanban)

Stakeholder & client-facing

  • Requirements gathering
  • Technical translation
  • Executive reporting
  • Customer-site delivery & commissioning
  • Mentoring

Data engineering

  • PostgreSQL (advanced)
  • AWS RDS Multi-AZ
  • Data modeling (OLTP/OLAP)
  • ETL/ELT pipelines
  • Large-scale datasets (1.4B rows)
  • SQL optimization
  • Redshift & dbt

Cloud & integration

  • AWS (EKS, RDS, Lambda, S3, QuickSight)
  • Kubernetes & K3s
  • Docker
  • REST APIs & middleware
  • Event-driven architecture
  • Kafka, Kinesis/MSK
  • Jira automation
  • Alerting & escalation design

Programming

  • Python
  • SQL
  • Java
  • C/C++
  • C#
  • Bash
  • Linux & Windows

Contact

Let's talk about the process you want automated.

Based in Tampa, FL. Happy to walk through how the vision-language pipeline was built, what it measures, and what it took to get it into production.

jpere682@gmail.com LinkedIn Download résumé (PDF)