') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ', 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); })(); farhoud (Farhoud) · GitHub
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Achievement: Pull Sharkx3Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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farhoud/README.md

Hi, I'm Farhoud 👋

Senior Full-Stack & AI/Data Engineer · Adana, Turkey
10+ years shipping production systems across aviation, legal-tech, Web3, real estate, and healthcare.

EmailLinkedIn

🧠 About Me

I build things end-to-end — from protocol-level Go services to LLM-powered pipelines to cross-platform mobile apps. I'm comfortable leading teams, architecting systems from scratch, and diving deep into whatever the problem demands.

Some highlights from my career:

  • ✈️ Built an AI-powered flight scheduling engine for Mahan Air (Vue.js, Python, gRPC, Neo4j)
  • 🤖 Shipped a multi-agent document intelligence platform handling 20+ GB of real estate documents per agency
  • 🔗 Joined as an early team lead at Functionland and led the pivot from JS to Go at the IPFS/libp2p protocol layer
  • 📊 Led the full ELK Stack migration for a large-scale real estate analytics platform
  • 🧬 Received a SingularityNET grant to implement scikit-learn-compatible ML algorithms in the MeTTa language

🛠️ Tech Stack

LanguagesPythonGoTypeScriptJavaScript

FrontendReactReact NativeVue.jsAngular

BackendNode.jsgRPC

DatabasesPostgreSQLElasticsearchNeo4jRedis

AI & DataLlamaIndexscikit-learnKafka

DevOpsDockerGitHub ActionsGitLab CILinux

💼 Experience

PeriodRoleCompany
Jun 2024 – PresentReact Native DeveloperMandegar Construction Co.
Jun 2020 – Jan 2024ELK Stack ConsultantMelk Radar
Aug 2021 – Sep 2022Team Lead, Storage & Protocol EngineeringFunctionland
Dec 2017 – Dec 2019Software Engineer — Full-Stack & DataMahan Air
Feb 2017 – Dec 2017Data Engineer & DevOpsMiras Technologies
Feb 2016 – Feb 2017Junior Web DeveloperSatratech

🚀 Key Projects

🏠 Real Estate AI Assistant (Contract, 2025)

Multi-agent RAG system built with LlamaIndex and parallel search strategies (fuzzy, BM25, vector) to handle 20+ GB of documents per agency. Replaced a single failing agent with self-improving retrieval logic that resolved critical accuracy failures threatening the product's viability.

🧬 SingularityNET ML Library (Grant, 2024)

Scikit-learn-compatible ML algorithm implementations in the MeTTa language, including Python bindings for seamless interoperability. Established the project repo, contribution guidelines, and data visualization utilities.

⚖️ Law Firm CMS Platform (Contract, 2023–2024)

Go backend services for a mass tort case management CMS — RESTful APIs, Twilio + Amazon Connect for outbound/inbound campaign automation, a contact resolution engine, and Amazon S3 integration for document storage.

🎓 Education

B.Sc. Software Engineering — Islamic Azad University (2015)

Open to senior full-stack, backend, or AI/data engineering roles. Feel free to reach out!

Pinned Loading

  1. scouterscouterPublic

    GraphRAG Agent API Monolith—FastAPI, Celery, and Neo4j combined for high-speed, asynchronous knowledge retrieval and ingestion.

    Python 1

  2. soverant/confidantsoverant/confidantPublic

    Go

  3. TankhahGardanTankhahGardanPublic

    TypeScript

  4. soverant/latticesoverant/latticePublic

    Python 1

  5. disez-ai/metta-uldisez-ai/metta-ulPublic

    Python 3 1