Software Engineer with 8+ years of experience building
production systems across government, e-commerce,
automotive logistics, and enterprise environments.
Primary focus:
→ Backend Engineering
→ Distributed Systems
→ Cloud-Native Architecture
→ Full-Stack Development
→ AI-Integrated Software
I build software where reliability, scalability, maintainability, and production behavior matter.
My engineering background spans enterprise government systems, real-time eCommerce services, and automotive inventory & logistics platforms.
Today, I’m increasingly interested in the intersection of traditional software engineering and reliable AI systems.
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Office of the State Comptroller |
Worked on enterprise government applications with a focus on modernization, backend development, database-driven workflows, production reliability, maintainability, security, and compliance.
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ShopRunner |
Backend engineering for ShopRunner One Click Checkout, supporting real-time eCommerce transactions through distributed services and APIs. Worked with Java/Spring-based services, microservices, cloud infrastructure, databases, and production systems where performance and reliability were critical.
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Automotive Systems |
Worked on enterprise applications supporting vehicle and automotive-parts inventory, logistics, and shipment tracking. The systems supported inventory visibility and movement of vehicles and parts between locations through logistics channels including road, air, and sea transportation.
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SQL · PL/SQL
Spring Boot · Spring · Hibernate · REST APIs · Microservices · GraphQL
EC2 · Lambda · ECS · S3 · RDS · SQS · SNS
Oracle · PostgreSQL · MongoDB · Redis · Kafka · Elasticsearch
CI/CD · GitHub Actions · Docker · Kubernetes
flowchart LR
A[Domain Context] --> B[Retrieval]
B --> C[LLM]
C --> D[Validation]
D --> E[Verification]
E --> F[Trusted Output]
D -->|Failure| B
I’m exploring ways to make AI systems more dependable in real applications, particularly around:
Retrieval-Augmented Generation
LLM Reliability
Hallucination Reduction
Domain-Aware AI
SQL Generation
Expert-System Validation
Multi-Stage Verification
AI Agents
The engineering problem that interests me most is not simply:
“Can an LLM generate an answer?”
but:
“How do we know the answer is reliable enough for another system to trust?”
AI-powered resume analysis and job-matching system
Evaluates resumes, identifies skill gaps, and compares candidate profiles against job descriptions.
Engineering focus
Java · Spring Boot · REST API · AI/NLP · React · Microservices
I’m actively expanding this GitHub with projects focused on:
- distributed Java/Spring Boot systems
- event-driven microservices
- cloud-native architecture
- production observability
- AI + backend integration
- RAG and AI verification
- engineering automation
- real-world system design
The goal is quality over repository count.
01 Distributed backend architectures
02 Event-driven systems
03 Cloud-native Java applications
04 RAG + hallucination reduction
05 AI-assisted software engineering
06 AI agents and verification pipelines
07 Production observability & reliability
public final class Engineering {
public static final String PRIORITY =
"Reliability > Complexity";
public static void build() {
designForFailure();
measureBeforeOptimizing();
automateRepetition();
writeMaintainableCode();
validateAIOutputs();
keepLearning();
}
}Build systems that still make sense when the original developer is no longer in the room.
