21 lines
3.1 KiB
Markdown
21 lines
3.1 KiB
Markdown
Dear Adobe Hiring Team,
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I am excited to apply for the Senior Software Engineer position (R170402) with the Brand Visibility team here in Basel. Building the systems that determine how enterprise brands appear in ChatGPT, Gemini, and the next generation of AI agents sits exactly at the intersection of my +20y background in full-stack software engineering and my recent work on AI-native platforms, LLM integrations, and web-scale content analysis.
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A representative example is my independent project, Rodado, the biggest Brazilian data platform maintaining and exposing ~730 Brazilian public datasets for analytics and AI. It manages approximately 1TB of Parquet data on S3-compatible storage, integrates DuckDB for analytics, provides REST APIs and semantic search, and includes an LLM-powered natural-language-to-SQL interface exposed through MCP tooling — making the entire platform directly consumable by AI agents. Building it required scalable ETL pipelines, robust metadata management, secure APIs, query optimization, and designing for exactly the kind of AI-driven discovery that brand visibility in AI experiences demands.
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I work AI-natively day to day: AI coding agents such as Claude Code are a core part of my development workflow, and I have built agentic systems end-to-end, including an autonomous framework that closes the loop between knowledge, hypothesis, experiment, and analysis. On the visibility side, my HelvetiScan project scanned and mapped 2.5M+ Swiss .ch domains — HTTP, DNS, TLS, WHOIS, and content — with sector classification and scoring, which is web presence analysis at national scale and the same class of problem as reasoning about brand visibility data across SEO/GEO platforms.
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Throughout my career, I have designed and delivered production systems using Python, TypeScript, Ruby, SQL/NoSQL databases, REST APIs, cloud infrastructure, CI/CD, and modern software engineering practices. At Swisscom, I helped modernize mission-critical internal platforms and CI/CD pipelines supporting high-availability telecommunications infrastructure. Previously, at EDGE Empower, I led a multidisciplinary engineering team, redesigned a Python monolith into a parallelized TypeScript architecture that reduced processing time by 98%, and shortened CI/CD pipelines from 14 minutes to 4 minutes — automated quality gates that scale without relying on individual discipline.
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I enjoy operating in ambiguity: as an independent consultant I drove 40+ projects from unclear briefs to shipped products, and I like sharing what I learn through mentoring, documentation, and teaching. I hold a Bachelor's degree in Computer Science, a Master's degree in Information Systems focused on knowledge representation and reasoning — a foundation that maps naturally onto how LLMs represent and retrieve knowledge about brands — and additional postgraduate studies in Data Science.
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I am based in Basel, immediately available, hold a Swiss B permit and a Portuguese passport.
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Thank you for your consideration.
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Kind regards,
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Rafael Polo
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14-July-2026
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extrapolo.com / linkedin.com/in/rafaelpolo / github.com/rafapolo
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