Senior Software Engineer

Wilfredo R. Ronsini Jr.

Building production software for industrial companies โ€” Java/Spring and Python backends, Angular/React frontends, AWS deployment, and applied AI at the core.

๐Ÿ“ Heidelberg, Germany ๐Ÿข WEISS GmbH
โฌ‡ Download CV Lebenslauf (DE) GitHub โ†— LinkedIn โ†—

About

The through-line

I'm a software engineer with 25+ years of experience designing and building production systems โ€” from IBM mainframe manufacturing in Brazil and the United States to cloud applications and applied AI in Germany.

At WEISS GmbH I built the backend of the product configurator that is live on the company's website and used daily by customers and the sales team. I work across Java/Spring, Python (Flask, FastAPI), Angular and React; I deploy to AWS and Heroku with Docker and CI/CD; and I build practical AI systems with LangChain โ€” RAG pipelines, LLM fine-tuning for text and images. My focus is software that an organisation actually depends on, not demos. I started in manufacturing and test engineering of IBM mainframes, where precision and quality at scale were non-negotiable โ€” and I bring that same systems rigour to every line of code I ship.


Technology

Core stack

Production-proven across backend, frontend, cloud, and AI layers.

Languages
Java Python TypeScript SQL
Frameworks
Spring Boot Flask FastAPI Angular React
Cloud & Infra
AWS Heroku Docker CI/CD PostgreSQL Cassandra
AI / ML
LangChain RAG LLM Fine-tuning OpenAI API IBM watsonx

Featured Work

Case studies

Selected projects โ€” each solving a real production problem.

Product Configurator ยท WEISS GmbH
Backend for an industrial product configurator used live by customers and the sales team
Designed and built the Java/Spring REST backend behind WEISS GmbH's web-facing configurator โ€” handling complex product logic, pricing rules, and real-time validation at production scale.
JavaSpring BootPostgreSQLAWSDocker
More projects โ†’
Applied AI ยท RAG Pipeline
Retrieval-Augmented Generation system for internal document search and Q&A
Built a production RAG pipeline in Python/LangChain connecting proprietary document stores to LLM inference โ€” cutting manual lookup time and surfacing answers that keyword search misses.
PythonLangChainRAGFastAPIOpenAI
Full AI page โ†’
LLM Fine-tuning ยท Image + Text
Domain-adapted LLM for industrial product classification and description generation
Fine-tuned a multimodal model on proprietary product data to generate accurate descriptions and classify components โ€” replacing a brittle rule-based system and reducing manual review.
PythonLLM Fine-tuningLangChainIBM watsonx
Full AI page โ†’

Explore

Three chapters

Each pillar is a distinct area of depth โ€” follow the one that matters to you.

๐Ÿค–
AI Applications
How I apply LLMs and RAG in production โ€” approach, evaluation methodology, and public project work. Includes a live demo.
Explore AI work โ†’
๐Ÿ–ฅ
Mainframe & Manufacturing
Test and product engineering on IBM mainframes โ€” the rigour I built before cloud. A differentiator, not a footnote.
Read the backstory โ†’
๐Ÿ“„
Contact & CV
Download my CV (English) or Lebenslauf (German), or reach out directly by email or LinkedIn.
Get in touch โ†’