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π Full Stack Engineer β’ AI Agent Architect
Building low latency backends, distributed systems, and multi agent AI orchestrations.
Systems engineer with a quantitative background in electricity market trading, analytics, and technical growth. Specializing in high throughput Python/Node.js backends, Kubernetes networking, and stateful multi agent AI systems using LangChain and LangGraph.
| Category | ToolKit |
|---|---|
| AI & Agentic Systems | LangGraph, LangChain, Agentic Workflows, MultiAgent Orchestration |
| Backend Engineering | Python (FastAPI, Django), Node.js (Express, Nestjs) |
| Frontend Engineering | Reactjs, Nextjs , Tailwind Css , Zustand, TanStack Query |
| Cloud & Infra | Docker, Kubernetes, Nginx, Aws (EC2, RDS, S3, CloudFront) |
| Data & Analytics | PostgreSQL / Pgvector, MongoDB, Postgis, Jupyter Notebooks, NumPy, Pandas |
| Testing & CI/CD | Pytest, Jest, Postman, GitHub Actions |
| Technical Growth | Technical SEO, PLG Analytics, HubSpot, Intercom |
Climate risk intelligence platform engineered for municipal bond underwriting, ESG compliance analysis, portfolio hedging, and multi agent risk assessment.
Orchestration: Leveraged LangChain for prompt formatting, tool calling definitions, and structured output parsing to ensure reliable communication between specialized agent nodes ( Risk Agent, Analytics Agent, and Actuarial Agent).
Tech Stack: LangGraph, LangChain, FastAPI, Nextjs, PostgreSQL/Pgvector , Gemini API, Docker.
Link:https://github.com/danishdynamic/Agentic-Climate-Risk-Asset-Underwriter-Green-Bond-Auditor
Product Demo:
Demo of Β agentic RAG platform for evidence backed sustainability research atΒ GreenTech Industries.
Contributed to core cloud native networking infrastructure within the CNCF landscape.
associated-node:update), enforcing strict least privilege access management across clusters.Improved production renewable energy predictability tooling used for grid level solar forecasting.
Designed a high throughput microservices architecture capable of handling concurrent event streams smoothly.
**Impact:**A full stack ML PropTech and climate finance platform that quantifies howΒ Urban Heat Island (UHI) microclimates and forecasted thermal anomalies impact commercial real estate (CRE) operating expenses (OpEx), Net Operating Income (NOI), and Discounted Cash Flow (DCF) asset valuations.
Tech Stack: FastApi, Nestjs, Reactjs, Quantlib, PostGis, Gradient boosting, Scikit Learn, Docker Compose, Kubernetes.
Link:https://github.com/danishdynamic/Urban-Heat-Island-Real-Estate-Asset-Pricing-Engine
Product Demo:
Demo of Climate aware real estate valuation engine using ML temperature forecasting, energy cost modeling, and DCF based property valuation.
Oct 2025 β Present | Remote (India)
Dec 2023 β Present | Remote (India)
Apr 2022 β Nov 2023 | Remote (Ljubljana / Boston)