I build production-grade Agentic AI systems — from multi-agent orchestration and self-healing pipelines to distributed ML infrastructure and RAG-powered assistants.
- 🤖 Focused on Agentic AI, Multi-Agent Systems, and LLM Application Engineering
- 🏗️ Building with MCP, A2A, gRPC, ReAct, RAG, and hybrid orchestration patterns
- 🌐 Strong foundation in Distributed Systems — consistent hashing, quorum replication, fault tolerance
- 🏥 Domain expertise spanning Healthcare AI, Drug Discovery, and FinTech
- 🔧 Experienced in shipping microservices, event-driven pipelines, and cloud-native ML systems
- 💬 Ask me about Agentic architectures, LLM tool use, distributed systems design, MLOps
| Project | Description | Stack |
|---|---|---|
| ChainMind | Multi-agent self-healing supply chain platform with ReAct orchestration & hybrid RAG | MCP · A2A · gRPC · Python |
| Multi-Agent Healthcare Workflow | End-to-end multi-agent AI system for clinical task automation | Python · LangChain |
| AI Web Search Agent | LLM agent with external tool integration, source retrieval & synthesis | Python · Tool Use |
| multica Issue Agent | Managed agent platform — assign tasks, track progress, compound agent skills | TypeScript |
| Project | Description | Stack |
|---|---|---|
| Distributed KV Core | Dynamo-inspired KV store with consistent hashing & OOP design | Python · MIT |
| Distributed KV Store | Fault-tolerant store with quorum replication & write-ahead logging | Makefile · Python |
| Microservices AI System | Java gateway + Python AI bridge with security & resilience layers | Java · Python |
| Scalable Claims Intelligence | Distributed ML pipeline for insurance cost prediction & anomaly detection | Python · Big Data |
| Project | Description | Stack |
|---|---|---|
| healthcare-GenAI-Guardian | Secure RAG assistant for clinical environments with PII masking | Python · RAG · NLP |
| Smart Document Q&A | PDF/text ingestion with LLM-grounded Q&A and source attribution | TypeScript |
| Synergex Med AI Call QA | HIPAA-compliant call QA system with agent performance monitoring | FastAPI · Gemini |
| AI Product Recommendation | Event-driven recommendation microservice | FastAPI · Kafka · Docker |
| Project | Description | Stack |
|---|---|---|
| mol_next_gen | Graph-based molecular generation | Python · GNN |
| Jepa Diffusion Generation | Geometry-aware molecule generation via JEPA + diffusion models | Python · MIT |
| Pharmacovigilance | Post-market drug surveillance system bridging FDA monitoring | Jupyter · Python |
| GAN AniFace | GAN experiments on facial datasets | Python |
name: R Nishanth
focus:
- "Agentic AI Systems (MCP, A2A, ReAct, Tool-Use)"
- "Distributed ML Infrastructure & MLOps"
- "RAG Pipelines & LLM Application Engineering"
- "Healthcare AI & Computational Chemistry"
open_to:
- "SDE roles in AI/Agent infrastructure"
- "ML Engineering & LLMOps"
- "Research Engineering in Agentic Systems"
hobbies:
- "Open Source (PyTorch, DeepChem, LangChain)"
- "Mentoring"
- "Cooking"
- "Exploring Emerging AI Architectures"- 📄 Research paper accepted at ICMED 2025 — "Japanese-to-English Video Dubbing Using BERT and Open Voice"
- 🎓 Selected participant in BITS Pilani Hyderabad AI/ML Workshop (2024)
- 🥈 Runner-Up at State-Level Technical Fest for innovative AI healthcare solution (2023)
- 🎤 Presenter at IEEE National-Level Project Expo (2024)
- 🌍 Active Open Source Contributor — PyTorch, DeepChem, LangChain
🔗 Open to collaborations on Agentic AI, distributed systems, and LLM engineering — connect on LinkedIn!