Srikrishna Pradeep Jorige

I'm a Senior Data Engineer with an MSc in Artificial Intelligence from Queen Mary University of London — a rare combination that lets me build systems where data engineering rigour and applied AI aren't separate disciplines.

My most significant work is the 3P SSOT system for Uber AI Solutions — the data engineering backbone of Uber's AI annotation supply chain. Tech giants like Google, Meta, Amazon, Microsoft, and Zoom use human-annotated data to train their AI models, outsourcing annotation tasks to vendors like Uber. I solely designed and built the system that consolidates all worker identity, task assignments, quality scores, billing rates, and vendor payments — previously scattered across dozens of disconnected spreadsheets — into one governed Hive data layer. It now powers an executive dashboard tracking 78 projects, $3.11M in revenue, and 94.96% quality across 237K+ annotation tasks. The identity-resolution architecture — a union-find graph with source-trust ranking across 8+ disjointed systems — was my own design.

Alongside the data platform work, I build AI products: Liftr AI — an agentic MCP-based platform for end-to-end data operations via conversational workflows — and the AI Data Modeling Assistant, a LangGraph agent that takes raw data and generates production-ready schemas across 10 modeling methodologies with a Pinecone RAG knowledge base.

I've led teams of 6–8 engineers, mentored 10+ freshers from zero industry experience to independent contributors, and spent a year as a Graduate Teaching Assistant at UCL alongside my MSc — running seminars, supervising dissertations, and building the habit of translating complexity into clarity.