ML Engineer at Accenture (R&D) building AI systems and enterprise frontend platforms. I care about reliability, observability, and shipping useful software fast.
Most of my delivery work is private, so the public repos here are reference implementations and exploratory builds around three themes: trustworthy RAG, ML observability, and micro-frontend platforms.
- GCP Professional Machine Learning Engineer (Credly)
- Portfolio: https://ramdragneel01.github.io/dragon-portfolio/
- LinkedIn: https://linkedin.com/in/ramprakashdhulipudi
- Medium: https://medium.com/@RamPrakashD
| Repository | What it is |
|---|---|
| partner-portal-microfrontends | Enterprise portal in federated React apps: Module Federation, Nx, RBAC, MSAL auth |
| hallucination-lens | Sentence-level RAG faithfulness scoring with a CLI |
| context-watchdog | Guardrails for long-running LLM and agent workflows |
| agentic-research-assistant | Multi-agent research with traceable orchestration |
| mlops-sentinel | Drift, latency, and reliability monitoring for models in use |
Python, FastAPI, LangGraph, TypeScript, React, Nx, Docker, PostgreSQL, GCP
Trustworthy RAG evaluation, MLOps reliability loops, and enterprise micro-frontend work. Best-effort reply within a few business days.
- GitHub: https://github.com/Ramdragneel01
- LinkedIn: https://linkedin.com/in/ramprakashdhulipudi
