AI Enablement Developer at Gcore | Torre
AI Enablement Developer
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Gcore

AI Enablement Developer

Gcore
Posted by
Roman Kapp
Emma
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Full-time
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Remote (for Poland residents)
Remote (for Cyprus residents)
Remote (for Lithuania residents)
Remote (for Serbia residents)
Posted 9 months ago

Responsibilities

What You’ll Do * Write code and ship agents by building resilient AI agents and backend scripts using Python and LangGraph. * Master data parsing by building sophisticated parsing agents to scrape, clean, and structure data from the web for lead enrichment and market intelligence. Ability to bypass anti-bot protections and handle unstructured HTML and JavaScript. * Orchestrate complexity by developing advanced workflows in n8n, including custom code nodes, error handling, and complex logic. * Educate and evangelize by running internal workshops and hackathons, acting as the AI champion who teaches other teams how to use AI for coding and automation. * Integrate systems by connecting platforms such as HubSpot, Jira, Airtable, and Clay through APIs, with a solid understanding of authentication, rate limits, and data consistency. * Collaborate closely with the Internal Business Analyst, who provides clear specifications in Mermaid and Markdown, allowing focus on architecture and implementation. Tech Stack * Core engineering: strong Python and SQL skills, with the ability to write clean and maintainable code. * AI development: daily use of Cursor or Claude Code, with strong expertise to review, debug, and optimize LLM-generated code. * Scraping and parsing: experience with libraries such as Beautiful Soup, Selenium, Playwright, or services like Apify or ScrapingBee. * Orchestration: deep knowledge of n8n, including custom nodes and expressions. * AI frameworks: experience with LangGraph, preferred, as well as LangChain or direct LLM API usage. * Tools: Git and basic SQL. Qualifications Not a fit if you * Think AI means only chatting with ChatGPT, as this role requires building and integrating AI into production code. * Cannot write code from scratch or rely entirely on low-code tools without understanding the underlying logic. * Do not prioritize quality, as statements like it works on my machine or the AI wrote it are not acceptable for production systems.
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