Professional Overview
I build LLM systems that survive production — SLAs, compliance, legacy stacks. At Serasa Experian (FTSE 100), architected an enterprise AI platform on MCP, serving 300+ engineers. 6 years backend: TypeScript/Node.js, C#/.NET, Java. RAG, agents, LLM orchestration. English C1. UTC-3, overlaps US/EU hours. Open to remote full-time or B2B contract.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected Codebuddy, enterprise AI platform on MCP (Model Context Protocol)
- Delivered LLM-powered skills into any IDE, standardized to company policy
- Built stack-specific AI assistants, PSA automation, and compliance workflows
- Build Java and Python backend services for high-volume credit systems (LGPD)
- Partner with Product, Data, and Risk teams on credit-decision APIs
Key Achievements / KPIs
- Drove platform adoption to 300+ engineers org-wide
- Innersource community: 10–15 contribution requests/week
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected scalable services and APIs in C#/.NET Core and Node.js/TypeScript
- Optimized SQL Server databases and queries for large-scale data operations
- Mentored junior developers and led code reviews, reducing technical debt
- Delivered end-to-end features (.NET backend + React) with product and UX teams
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Delivered RESTful APIs in TypeScript/Node.js with SQL Server and MongoDB
- Containerized services with Docker/Kubernetes, enabling CI/CD pipelines
Education
Field of Study: AI Engineering
Field of Study: Computer Engineering
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
