Jul 2020 – Present
United Nations · Senior Full Stack Developer
772M+
Documents Indexed
Hybrid
Keyword + Vector Search
6
UN Languages
AI
LangGraph Doc Assistant
~60%
API Response Time Reduced
30+
Manual Workflows Eliminated
1000s
Real-time Synced Users
At the United Nations, I worked as a Senior Full Stack Developer on a suite of mission-critical linguistic and document platforms used globally by translators, editors, diplomats, and researchers. These systems power translation, editing, search, terminology management, and document accessibility across multiple languages and global offices. They run search at internet scale — a production Elasticsearch estate whose largest clusters hold ~772 million and ~100 million documents, plus Azure AI Search across 16 UN duty stations worldwide — with hybrid keyword + vector retrieval feeding a production multilingual RAG assistant — a LangGraph ReAct chatbot (FastAPI + Azure OpenAI) that answers natural-language questions over official UN documents and voting records across all six official languages.
Legacy REST APIs limiting flexibility and performance
Massive multilingual datasets across documents and terminology
Fragmented tools for translation, editing, and search
Need for real-time collaboration between translators and editors
Difficulty in making documents machine-readable and searchable
Searching hundreds of millions of multilingual documents with relevance
Limited AI assistance in translation and document retrieval workflows
Replaced legacy REST APIs with GraphQL-based architecture
Built AI-powered tooling for translation assistance
Built a production multilingual RAG chatbot (FastAPI + LangGraph ReAct + Azure OpenAI) answering questions over UN documents and voting records
Transcribed recordings of UN speeches into the 6 official languages via AWS Transcribe, orchestrated by Python Azure Functions
Enhanced multilingual search and document retrieval systems
Developed structured document conversion pipelines (Word → XML)
Improved collaboration workflows between translators and editors
Integrated terminology intelligence (UNTERM) into translation flow
Operated Elasticsearch at scale with custom multilingual analyzers and relevance tuning
Built hybrid keyword + vector retrieval feeding a LangGraph ReAct document assistant
Built ETL pipelines into a data warehouse with SSRS reporting, Power BI dashboards, and DAX measures
Designed and implemented GraphQL APIs replacing legacy REST systems
Built and enhanced features across translation, editing, and search platforms
Developed document conversion pipeline (Word → structured XML / AKN4UN)
Improved performance and scalability of large document systems
Integrated AI capabilities into existing platforms
Built cross-cloud speech transcription: Python Azure Functions calling AWS Transcribe to transcribe UN speeches into 6 languages
Operated production Elasticsearch at scale (7 clusters, ~772M documents in the largest)
Built hybrid keyword + vector search and a LangGraph ReAct document assistant
Built the production multilingual RAG chatbot (FastAPI, LangGraph, Azure OpenAI, Azure AI Search) over UN documents and voting data
Built ETL pipelines into a data warehouse feeding SSRS reports and Power BI dashboards (DAX)
Collaborated with product managers, UX teams, and domain experts
Contributed to frontend systems using Vue.js
Wrote automated tests (unit, integration, Selenium)
Supported DevOps workflows on Azure
Migrated multiple systems from REST to GraphQL architecture
Built AI-powered translation assistant used in production workflows
Enabled machine-readable UN documents through structured XML conversion
Operated Elasticsearch at internet scale — ~772M documents in the largest cluster
Delivered hybrid keyword + vector retrieval feeding a LangGraph document AI assistant
Shipped a production RAG chatbot answering natural-language questions over UN documents and voting records in 6 languages
Met SLA-backed 99.9% uptime for the governments and inter-governmental organizations relying on the platforms
Enhanced real-time collaboration between translators and editors
Contributed across multiple mission-critical UN platforms
Improved efficiency of translators through automation and AI assistance
Enabled better access to global UN documents for public and internal users
Increased system scalability and maintainability through API modernization
Reduced complexity in querying large multilingual datasets
Enhanced consistency and accuracy of translations using terminology systems
Supported global users working across multiple languages and regions
Sustained SLA agreements and 99.9% uptime with member states, inter-governmental, and government organizations
Backend
C#, .NET, GraphQL, REST, WCF/SOAP (legacy services)
Frontend
Vue.js
Cloud
Azure
Data
SQL Server, XML
Data Eng
SSRS, ETL, Data Warehouse, Power BI, DAX
Search
Elasticsearch (7 clusters, ~772M docs), Azure AI Search, hybrid keyword+vector
AI
Python, FastAPI, LangChain, LangGraph (ReAct), Azure OpenAI (GPT-4o-mini), Azure AI Search (semantic hybrid), Azure AI Foundry, Managed Identity, MongoDB
Chatbot
Multilingual RAG, multi-agent tools, voting-data SQL agent, LibreChat UI, OpenAI-compatible streaming
Speech
AWS Transcribe (6-language), Azure Functions, Azure Key Vault
Networking
VNET, private endpoints, VPN
Testing
xUnit, Selenium, Integration Testing
DevOps
Azure DevOps, Terraform, Azure Bicep (IaC)
Observability
Application Insights (consolidated from Seq)
High-performance APIs and microservices
Stripe, Shopify, Microsoft Graph, telecom
LLM workflows, document processing
OAuth, Entra ID, Cognito
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