Hi, I’m Pedro, a software engineer with 4+ years building and scaling production web applications using TypeScript, React, Python, and AWS. I enjoy designing robust systems, optimizing performance, and implementing secure backend architectures that help services achieve high uptime and noticeable performance gains. I’ve been hands-on with applied AI systems, including LLM integration and RAG pipelines, turning complex AI capabilities into reliable production features and writing production-grade code that is easy to maintain and audit.

Pedro Oliveira

Hi, I’m Pedro, a software engineer with 4+ years building and scaling production web applications using TypeScript, React, Python, and AWS. I enjoy designing robust systems, optimizing performance, and implementing secure backend architectures that help services achieve high uptime and noticeable performance gains. I’ve been hands-on with applied AI systems, including LLM integration and RAG pipelines, turning complex AI capabilities into reliable production features and writing production-grade code that is easy to maintain and audit.

Available to hire

Hi, I’m Pedro, a software engineer with 4+ years building and scaling production web applications using TypeScript, React, Python, and AWS. I enjoy designing robust systems, optimizing performance, and implementing secure backend architectures that help services achieve high uptime and noticeable performance gains.

I’ve been hands-on with applied AI systems, including LLM integration and RAG pipelines, turning complex AI capabilities into reliable production features and writing production-grade code that is easy to maintain and audit.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert

Language

Amharic
Intermediate

Work Experience

Machine Learning Engineer — Software & AI Systems at Revelo
January 1, 2026 - Present
Selected for an invite-only ML engineering role training LLMs for production-grade software development tasks. Reviewed and scored 300+ complex code generations, improving execution accuracy and reasoning reliability by 25%. Delivered structured feedback that measurably reduced logic errors and invalid assumptions in multi-step AI outputs.
Machine Learning Specialist — Software Engineering Domain at Outlier
January 1, 2025 - January 1, 2026
Evaluate and debug LLM-generated code across Python and JavaScript, improving executable pass rates by 20-25%. Identify recurring logic and reasoning flaws in multi-step outputs, reducing error frequency by 15%. Refine prompt structures for technical tasks, minimizing hallucinations and invalid assumptions in evaluation workflows.
Software Engineer (Freelance) at Freelance / Self-Employed
June 1, 2021 - December 1, 2024
Delivered 5 production web applications for education and productivity clients, maintaining 99%+ uptime on AWS and Supabase infrastructure. Reduced frontend load times by 50-70% through code splitting, lazy loading, and optimized caching, directly improving user engagement. Architected AI features including RAG pipelines and chat interfaces used by 500+ active users across multiple client applications. Implemented security best practices: Row-Level Security policies, IAM roles, and KMS encryption for sensitive data protection.
Project Lead — StudyShield AI-Powered Study Platform at StudyShield
October 1, 2025 - Present
Implemented hybrid AI architecture (Gemini Flash + Nano) achieving 50% lower latency compared to cloud-only approach. Built complete offline mode using service workers and on-device inference, reducing backend API calls by 80%. Architected secure multi-tenant backend with Supabase RLS policies ensuring complete data isolation across 100+ users. Optimized bundle size and caching strategy to achieve sub-1-second initial page loads on modern devices.
Freelance Software Engineer at Independent Contractor (Remote)
June 1, 2021 - December 1, 2024
Delivered 5 production web applications for education and productivity clients, maintaining 99%+ uptime on AWS and Supabase infrastructure. Reduced frontend load times by 50-70% through code splitting, lazy loading, and optimized caching. Architected AI features including RAG pipelines and chat interfaces used by 500+ active users across multiple client applications. Implemented security best practices: Row-Level Security policies, IAM roles, and KMS encryption for sensitive data protection.

Education

B.S. in Systems Analysis and Development at Estácio University
January 11, 2030 - January 1, 2026
Harvard CS50x, CS50 AI, CS50 Cybersecurity Coursework at Harvard University
January 11, 2030 - January 4, 2026
B.S. in Systems Analysis and Development at Estácio University
January 11, 2030 - January 1, 2026

Qualifications

Harvard CS50x, CS50 AI, CS50 Cybersecurity Coursework
January 11, 2030 - January 4, 2026

Industry Experience

Software & Internet, Professional Services, Education