Python / FastAPI / React / TypeScript / RAG / Kubernetes

Full-stack systems that feel fast at every layer.

I build product experiences from interface to infrastructure: typed React front ends, secure Python APIs, GenAI/RAG workflows, reliable data layers, containerized releases, and observability that keeps real user journeys visible after launch.

GitHub LeetCode Project Proof
frontend React, TypeScript, responsive UI
api FastAPI, Django, Flask, OAuth2/JWT
data PostgreSQL, MongoDB, Redis, vectors
ship Docker, Kubernetes, CI/CD, clouds

Product Engineering

Interfaces, APIs, data, and AI working as one path.

The work I keep choosing is the part where a good idea becomes dependable software: clear interfaces, measured latency, trustworthy auth, useful retrieval, and releases that keep getting easier to operate.

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Recommendation lift

Embedding similarity and RAG improved candidate matching in agentic hiring workflows.

0 ms

p95 render target

React + TypeScript dashboards stayed responsive across daily recruiter sessions.

0 K+

Monthly requests

Kubernetes services scaled with caching, persistence, horizontal autoscaling, and CI/CD.

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Incident reduction

Testing strategy, code reviews, Jenkins pipelines, and delivery discipline lowered production risk.

Architecture Diagram

Full-stack delivery loop from user action to observable release.

A practical architecture for modern product work: typed UI, secure API boundaries, persistence, retrieval-augmented AI, container delivery, and feedback from production.

Python full-stack application architecture React and TypeScript clients connect to secure Python APIs, data stores, RAG workflows, deployment platforms, and observability feedback. React client TS | auth | polling Python API FastAPI | Django | Flask State + cache Postgres | Mongo | Redis RAG layer OpenAI | tools | vectors Cloud runtime K8s | Azure | AWS logs | metrics WORK I KEEP CHOOSING make the user path feel simple because the system is solid CI/CD test | image | deploy

Experience

Python full-stack systems, GenAI workflows, and cloud delivery.

Mar 2025 - Present Chicago, IL

Sprouts AI

Software Engineer (Python / GenAI / Full Stack)

  • Built an AI hiring agent backend in Python (FastAPI) with multi-step agentic workflows - orchestrating LLM calls (OpenAI Responses API), tool-use for ATS (Greenhouse) and calendar integrations, and prompt/context engineering across candidate matching, screening Q&A, and scheduling - boosting recommendation accuracy 35% via embedding-based similarity scoring and RAG over candidate profiles.
  • Developed React + TypeScript recruiter dashboards integrating with FastAPI REST endpoints - reusable components, real-time polling, secure auth flows (OAuth2/JWT) - sustaining sub-800ms p95 render times across 1K+ daily user sessions.
  • Implemented an MCP (Model Context Protocol) server exposing recruiting tools and read-only resources via JSON-RPC - fixed a duplicate-tool-call bug from session retries by adding idempotency keys (workflowId + eventType + version) and separating state-changing tools from side-effect-free MCP resources.
  • Deployed services on Azure with Docker multi-stage builds and Kubernetes - used Azure Functions for event-driven jobs, Azure Container Apps for long-running agent containers, and Azure AI Search for hybrid vector + keyword retrieval, with environment-config separation across dev/staging/prod.
Aug 2023 - Mar 2025 Chicago, IL

Resilience Inc

Software Engineer (Python / React / Full Stack)

  • Built full-stack features in React + TypeScript front ends and Python (FastAPI) / Node.js backends - REST API integration, ML-driven personalization, and modern UI patterns lifted user engagement 40% and reduced page load 30%.
  • Integrated GenAI prompt-driven content generation flows with vector embedding-based recommendations - applied feature engineering and ranking algorithms to surface contextually relevant content over learner-engagement signals.
  • Engineered Docker / Kubernetes deployments with Redis-backed caching, MongoDB document stores, and PostgreSQL persistence - scaled to 500K+ monthly requests with horizontal autoscaling and CI/CD via GitLab CI and GitHub Actions.
Apr 2018 - Aug 2023

Tata Steel

Software Engineer (Python / Backend / Cloud)

  • Architected microservices in Python (FastAPI) and Java (Spring Boot) on AWS, Azure, and OpenShift with Docker and Kubernetes - achieving 99.99% uptime and 40% faster API response times for 40K+ users across 5+ business domains.
  • Implemented embedding-based search and recommendation features in training systems with PostgreSQL/MongoDB persistence; led a 12-person engineering team through full Agile SDLC with code reviews, JUnit/PyTest test strategy, and Jenkins-based CI/CD - cutting production incidents 50%.

Project Evidence

Code that spans apps, AI, data, and systems fundamentals.

Demo and source links are separated whenever a live demo exists.

Full-Stack RAG

AskMyStore

End-to-end RAG application with React frontend, FastAPI backend, document ingestion, vector embeddings, semantic retrieval, and grounded LLM Q&A.

PythonFastAPIReactVector Search
Demo Source code

Trading Dashboard

TradeSentinel

Market-aware dashboard focused on signal visibility, portfolio state, active monitoring, and practical decision support workflows.

DashboardSignalsMonitoring
Demo Source code

Agentic AI

LangChain Chat with Search

Agentic LLM application with multi-tool orchestration, web search, Wikipedia API usage, zero-shot reasoning, and fusion prompting.

PythonLangChainTools
Source code

Streaming Analytics

Real-time Stock Market Analysis Pipeline

Streaming data pipeline shaped around ingestion, transformation, and analytics-ready market signals.

StreamingPipelineAnalytics
Source code

Low-Latency Systems

CME MDP 3.0 Multicast Feed Handler

C++ feed handler focused on packet processing discipline, throughput, and reliable market data handling.

C++NetworkingMarket Data
Source code

Publication

IEEE Movie Recommendation Study

Comparative study across collaborative, content-based, and hybrid recommendation models with feature engineering and error-function improvements.

ResearchEvaluationRecommenders
Paper Source code Certificate

Operating Systems

EXPOS

Experimental operating system work covering process control, memory, system calls, and low-level debugging.

OSSystemsDebugging
Source code

Kernel Programming

Character Device Driver

Linux character device driver implementation focused on kernel interfaces, file operations, and systems testing.

CLinuxKernel
Source code

Application

STRANGERS

End-to-end application project demonstrating backend structure, product thinking, and user-facing delivery.

BackendApplicationDelivery
Source code

Hardware Design

16-Bit RISC Processor

Computer architecture lab project covering datapath design, instruction execution, and digital logic fundamentals.

RISCArchitectureLogic
Source code

iOS App

Pitch Perfect

iOS application focused on audio interaction, mobile UI flow, and Swift application fundamentals.

SwiftiOSAudio
Source code

Technical Range

Stack I use to keep product systems fast, secure, and useful.

Python 3 FastAPI Django Flask Pydantic SQLAlchemy React TypeScript Redux OAuth2/JWT REST APIs GraphQL OpenAI API Azure OpenAI LangChain RAG MCP PostgreSQL MongoDB Redis Docker Kubernetes Azure AWS GCP GitHub Actions GitLab CI Jenkins OpenTelemetry