Open to opportunities

Thomas Galica

@thomasgalica

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AI-focused full-stack developer specializing in GenAI, NLP, and scalable systems.

United States

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What I'm looking for

I seek senior engineering roles focused on GenAI/NLP productionization, scalable systems, collaborative remote teams, mentorship, and opportunities to lead technical architecture and accelerate deployment of ML-driven products.

I am an AI-focused full-stack developer with 12 years of experience building and deploying machine learning models and scalable web systems. I specialize in GenAI, NLP, TTS, multimodal systems, and production-grade microservice architectures.

At O'Shaughnessy Asset Management I led a remote team of 10 engineers, built end-to-end tax calculation systems with Django and Flask, and architected microservices using FastAPI, RabbitMQ, and Kafka to improve scalability and latency.

Previously, I improved AI-based fraud detection and machine learning pipelines at Travelers, executed compliance and DevOps solutions at EpiCenter ERP, and built user-facing platforms and cloud infrastructure earlier in my career. I regularly implement Terraform, AWS services, and CI/CD to automate deployments and reduce manual interventions.

I emphasize collaboration, mentorship, and best practices—conducting peer code reviews, enforcing SOLID principles, and promoting test-driven development—to reduce technical debt and ship reliable, secure solutions in fast-paced and remote environments.

Experience

Work history, roles, and key accomplishments

Current

Lead Software Developer

Current

O'Shaughnessy Asset Management

Sep 2021 - Present (4 years 2 months)

Spearheaded development of AI-based tax calculation models improving accuracy by 5% and reduced cloud computation time by 11% through AWS Lambda integrations; led a remote team of 10 engineers and cut project delivery times by 7% using Agile practices.

Python TensorFlow Django Flask fastAPI AWS Lambda RabbitMQ Kafka Terraform Pytest

Software Engineer

Travelers

Jul 2018 - Jul 2021 (3 years)

Improved AI-based fraud detection accuracy by 8% using Python and scikit-learn and introduced TensorFlow ML pipelines that raised claim decision accuracy by 10%; implemented React/Redux front-ends and optimized backend ASP.NET/PostgreSQL services to boost efficiency.

Python scikit learn TensorFlow ReactJS Redux TypeScript MongoDB ASP.NET PostgreSQL Machine Learning

Senior Software Developer

EpiCenter ERP

May 2015 - Jun 2018 (3 years 1 month)

Delivered .NET Core military compliance solutions reducing audit processing times by 8% and automated CI/CD with Jenkins, Docker, and Kubernetes, cutting deployment failures by 9% while improving infrastructure scalability via Azure.

.NET Core Azure Jenkins Docker Kubernetes DevOps & Security CI CD SOLID Code Review

Software Developer

FPI

May 2012 - May 2015 (3 years)

Built a dynamic interest rate comparison platform with Python/Flask and MongoDB that increased user engagement by 6% and improved processing efficiency by 7%; implemented front-end enhancements raising interaction rates by 8%.