ใ โ ย UNLIMITED VOID ย โ ใย โย whoami
const ashutosh: CursedTechnique = {
name: "Ashutosh Yadav",
location: "Dublin, Ireland ๐ฎ๐ช",
education: "MSc Computer Science @ University College Dublin",
role: "Full Stack Software Engineer",
domain: "โ Throughout Terminals and Deploys, I Alone Push to Production โ",
stack: ["Python / FastAPI", "React / Next.js", "AWS", "Docker", "PostgreSQL"],
interests: ["FinTech", "AI Systems", "Distributed Architecture", "Data Engineering"],
experience: ["Capgemini โ Software Engineer", "Morningstar โ Data Analyst"],
available: "Internship opportunities from June 2026",
};|
๐ SnapSearch
Semantic Search Engine RAG pipeline using Florence-2 vision model for multi-modal embedding generation. Sub-millisecond vector retrieval via FAISS HNSW indexing. Fully containerised on Docker. โ View Project |
๐ Econometric Pipelines
Financial Time-Series Analysis Automated data pipelines for macroeconomic forecasting. Applied ARIMA & VAR models to model inflation dynamics. Structured outputs for financial decision-making. โ View Project |
|
๐ค Local LLM Stack
Private AI Deployment Infrastructure Self-hosted LLM environment (Llama 3, Mistral) via Ollama & Docker. Python API wrappers for internal text processing. Scripted for rapid deployment and team adoption. |
Distributed Booking System High-concurrency booking engine with event-driven architecture via RabbitMQ. ACID-compliant data integrity. Full microservices setup with Spring Boot. โ View Project |
|
๐ค Corporate Finance Autopilot
Agentic AI Finance Platform Agentic AI loop powered by Llama 3.3 70B with autonomous tool-calling, RAG over SEC filings via pgvector, DCF/WACC financial engine, and real-time WebSocket streaming. Deployed on Google Cloud Run with CI/CD via Cloud Build. โ Backend ยท โ Frontend ยท โ Live Demo |
| Role | Company | Highlights | |
|---|---|---|---|
| โ๏ธ | Software Engineer | Capgemini | Enterprise SaaS ยท Sony & Universal ยท Backend automation |
| ๐ | Data Analyst Associate | Morningstar, Inc. | Corporate finance data ยท Routing efficiency ยท Data reliability |



