Thomas Galica

Senior Software Engineer (Web & AI)

Southampton, United States

Summary

•An AI-focused full-stack developer with 12 years of experience in building and deploying machine learning models, along with expertise in Python and ASP.NET technologies, cloud solutions, and microservices architectures.

•Specialized in GenAI, NLP, TTS, and multimodal systems, with proven success in deploying advanced RAG pipelines, fine-tuning large-scale speech synthesis models, and achieving 10x latency reductions for real-time AI applications.

•Experienced in remote work environments and startup settings, contributing to fast-paced projects with a focus on innovation and agility.

•Leadership skills, with experience guiding teams in creating scalable solutions while promoting collaboration and mentorship to enhance team productivity and project outcomes.

Languages:

English

Favorite Python Packages:

TensorFlow, PyTorch, scikit-learn, Keras, XGBoost, LightGBM, Django, Flask, FastAPI, Requests, BeautifulSoup, Selenium, Gunicorn, Tornado, Celery, SQLAlchemy, Pyramid, Cherrypy, Mako, Jinja2, Werkzeug. Matplotlib, Seaborn, OpenCV, spaCy, NLTK, Transformers, Gensim.

Experience

Lead Software Developer

O'Shaughnessy Asset Management

09/2021 – Present | Remote

• •Spearheaded the development of AI-based tax calculation models, improving calculation accuracy by 5%, leveraging Python, TensorFlow, and custom algorithms for predictive modeling.

• •Led a remote team of 10 engineers, ensuring seamless collaboration and reducing project delivery times by 7% by adopting Agile methodologies and utilizing tools like Jira and GitHub.

• •Developed end-to-end tax calculation systems using Django and Flask, integrating AWS Lambda to enhance cloud performance, reducing computational time by 11%.

• •Architected and implemented microservices using FastAPI, RabbitMQ, and Kafka, improving system scalability and reducing latency by 9%.

• •Integrated secure cloud storage solutions using AWS S3 and Terraform, automating deployment and reducing manual intervention by 10%.

• •Conducted peer code reviews by ensuring adherence to design patterns, best coding practices, and robust testing frameworks like Pytest and Jest reducing technical debt by 7%.

 

 

Software Engineer

Travelers

07/2018 – 07/2021 | Hartford, CT

• •Improved AI-based fraud detection systems using Python and Scikit-learn, improving detection accuracy by 8% in processing insurance claims.

• •Implemented ReactJS and Redux for front-end user interfaces, enhancing the user experience by 4% as measured by user feedback and internal metrics.

• •Managed the development of a custom staff management system, utilizing TypeScript and MongoDB for database architecture, improving internal operational efficiency by 9%.

• •Enhanced backend services with ASP.NET and PostgreSQL, optimizing data retrieval speeds by 6% in real-time insurance claim processing.

• •Introduced machine learning pipelines using TensorFlow, improving decision-making accuracy by 10% in claim assessments and risk analysis.

 

 

Senior Software Developer

EpiCenter ERP

05/2015 – 06/2018 | San Diego, CA

• •Executed a military compliance solution using .NET Core, reducing compliance audit processing times by 8% through optimized architecture and code refactoring.

• •Automated the deployment pipeline using Jenkins, Docker, and Kubernetes, leading to a 9% reduction in deployment failures and ensuring consistent delivery across environments.

• •Collaborated with DevOps teams to integrate cloud services with Azure, resulting in a 5% improvement in infrastructure scalability and reliability.

• •Directed complex security protocols for military and aerospace compliance systems, ensuring adherence to government security standards and reducing vulnerabilities by 8%.

• •Contributed to code reviews, improving software quality and reducing defects in production by 10% by enforcing SOLID principles and clean code practices.

 

 

Software Developer

FPI

05/2012 – 05/2015 | Springfield, MA

• •Enforced a dynamic interest rate comparison platform using Python, Flask, and MongoDB, improving user engagement by 6% and processing efficiency by 7%.

• •Enhanced frontend interfaces with HTML, CSS, and JavaScript, boosting user interaction rates by 8% as tracked by web analytics tools.

• •Applied cloud-based infrastructure using AWS S3 and EC2, reducing server costs by 5% and ensuring faster page load times for users.

• •Created automated test suites using Jest and Mocha, reducing testing time by 6% and increasing code coverage by 8%.

• •Collaborated with cross-functional teams to integrate front-end and back-end solutions, improving system efficiency and reducing development time by 10%.

Skills

Amazon Web Services (AWS), Big Data, Data Science, Docker, Keras, Web Development, Web Scraping