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Thiago Thomas

@thiagothomas

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Msc Computer Science Student | Backend | Java, Spring Boot, JavaScript, TypeScript | AI Research

Brazil

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What I'm looking for

I’m looking for a company that embraces the latest technologies, fosters collaboration with top professionals, and values ownership and flexibility.

𝗠𝘀𝗰 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 student specializing in 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 and 𝗚𝗼𝗮𝗹 𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻. Passionate about AI research and its real-world applications. 𝗙𝘂𝗹𝗹-𝗦𝘁𝗮𝗰𝗸 Software Engineer with a strong 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝗳𝗼𝗰𝘂𝘀, dedicated to building high-quality, efficient systems that enhance user experience. Committed to solving.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

SAP

Nov 2021 - Present (3 years 9 months)

Designed and developed new features in SAP Ariba Procurement, including supplier anonymization and adapting existing features for public sector requirements. Engaged in full-stack development.

Java Spring Boot Angular TypeScript Full Stack Developer

Java Developer

NTT DATA Europe & LATAM

Jul 2021 - Nov 2021 (4 months)

Developed Open Banking/Open Finance microservices for Itau Unibanco, implementing AWS SQS for Open Banking consents and utilizing Hexagonal Architecture.

Java Spring Boot Kafka AWS SQL Scrum TDD

Junior Java Developer

Education

Degrees, certifications, and relevant coursework

Pontifícia Universidade Católica do Rio Grande do Sul

Master of Science, Computer Science

2025 - 2026

Pursuing a Master's degree in Computer Science with a research focus on Artificial Intelligence, specifically in Multi-Agent Reinforcement Learning and Goal Recognition.

Universidade do Vale do Rio dos Sinos

Bachelor of Science, Computer Science

2020 - 2024

Activities and societies: Technologies used: Java, Quarkus, Python, AWS (EC2, SQS, Lambda, API Gateway, S3, CloudWatch)

Pursued a Bachelor of Science in Computer Science, participated in Undergraduate Research in Reinforcement Learning, and completed a thesis on exploring serverless technology and loading strategies in vital sign analysis with fog computing.