Available for full-time, freelance & consulting

Software that holds up in production.

Bhargav Patel — Senior Full Stack & Data Engineer, AI & Cloud

I build scalable Python backends, AI/LLM systems, and cloud-native data platforms — 4+ years shipping production software on AWS and Azure, from multi-tenant SaaS to Medallion-architecture data estates.

Start a conversation Resume PDF ↗

GitHub /bhargav2800 LinkedIn /bhargavpatel2404 X @BhargavPyDev Blog tech notes

>>> from engineer import Bhargav

>>> bhargav = Bhargav(
...     role   = "Senior Full Stack & Data Engineer",
...     focus  = ["python_backends", "ai_systems", "cloud"],
...     stack  = ["Django", "FastAPI", "LangChain", "AWS", "Azure"],
... )

>>> bhargav.years_shipping
4

>>> bhargav.status
'open_to_work'

4+years shipping production software

10+projects delivered end to end

60+technologies across the stack

6+clients served

Selected work

Three projects that show the range — machine learning in production, an enterprise data platform, and generative AI applied to real content. Titles link to the full case studies.

01 AI / Machine Learning Completed

Intelligent Data Deduplication & Clustering Platform ↗

Eliminate data-quality issues across a large document corpus by detecting duplicate records, clustering similar entities, and letting human reviewers teach the model to get better over time.

What it does

Custom dedup algorithm — TF-IDF + cosine similarity finds likely duplicates and groups them into reviewable clusters.
FastAPI processing backend handles data processing and model integration at scale.
Next.js review UI where the team approves or rejects matches to keep data quality moving.
Feedback-driven retraining turns every human correction into an automated learning loop.

80% of duplicates removed 50K+ documents in the corpus Self-improving via review feedback

FastAPINext.jsPythonMachine LearningPostgreSQLREST APIs

02 Data Engineering Completed

Data Platform with Medallion Architecture ↗

A production-grade data engineering platform on Microsoft Fabric, delivering reliable, analytics-ready data for enterprise Power BI reporting.

What it does

Automated pipelines ingest and transform data from multiple sources on a scheduled basis.
Bronze → Silver → Gold layering follows Medallion Architecture best practices end to end.
Git-based version control inside Fabric keeps pipelines and workspaces manageable.
Warehouse models & Power BI dashboards turn the Gold layer into business insight.

Enterprise Power BI reporting Scheduled multi-source ETL Governed via Git in Fabric

Microsoft FabricPySparkSQLPythonLakehousePower BI

03 Web Application · GenAI Completed

AI-Driven Book Authoring Platform ↗

Modernize traditional books with AI — users upload, write, and update books while generative AI restyles content, designs covers, and breathes new life into old material.

What it does

Django platform for uploading, authoring, and editing books with a TinyMCE editor.
Legacy migration brought old books in through Azure Blob Storage and the Watcher API.
Generative AI — Fooocus and OpenAI APIs enhance content and generate covers; LangChain + ChromaDB vectorize it for retrieval.
Multi-agent orchestration generates complete AI-authored books from uploads or PDFs, on an Azure VM built for scale.

65% faster content production End-to-end AI book generation Legacy library migrated

DjangoPostgreSQLLangChainOpenAIChromaDBAzureTinyMCEWebSocket

Experience

A progression from building features to leading teams through production deployments on AWS and Azure.

Senior Full Stack & AI Engineer

AI systems · data platforms · team leadership

Built an LLM authoring platform with multi-agent orchestration, cutting content production time by 65%.
Designed a Microsoft Fabric data platform on Medallion Architecture with PySpark and Power BI.
Created an ML deduplication engine (TF-IDF + cosine similarity) removing 80% of duplicates across a 50K+ document corpus.
Led the team through deployment on AWS (EC2, S3, RDS, CloudWatch) and Azure (AKS, CosmosDB).

PythonLangChainMicrosoft FabricAWSFastAPIOpenAI

Full Stack Developer

SaaS backends · real-time systems · CI/CD

Built a multi-tenant SaaS backend (Django REST Framework + PostgreSQL) serving 10K+ concurrent users at 99.9% uptime.
Shipped a real-time React + WebSocket analytics dashboard with sub-200ms latency.
Cut deployment time from 2 hours to 12 minutes with Jenkins, Docker, and Terraform CI/CD.
Integrated Stripe, Twilio, and AWS SNS across billing and messaging flows.

DjangoReactPostgreSQLDockerRedisCelery

Software Engineer

Data pipelines · APIs · web performance

Built Scrapy + BeautifulSoup scrapers aggregating data from 200+ sources into MongoDB via ETL.
Added a GraphQL layer over legacy REST, cutting over-fetching by 70%.
Shipped a Next.js SSR storefront and took its Lighthouse score from 48 to 92.

PythonScrapyGraphQLNext.jsMongoDBFastAPI

Skills

60+ technologies across eight working areas — these are the tools that show up in the projects above.

Languages · 6

PythonSQLJavaScriptTypeScriptHTMLCSS

Frameworks & Libraries · 8

DjangoDRFFastAPIReactNext.jsGraphQLLangChainLlamaIndex

GenAI & LLMs · 8

OpenAIGeminiMistralAIHuggingFaceLangChainLlamaIndexChromaDBMulti-agent

Cloud & DevOps · 8

AWSAzureDockerTerraformJenkinsCI/CDCloudWatchIIS Server

Data Engineering · 7

Apache AirflowMicrosoft FabricMedallion ArchitecturePySparkDuckDBStreamlitPower BI

Databases · 8

PostgreSQLMySQLMongoDBDynamoDBRedisOpenSearchCosmosDBElasticSearch

Data Science & ML · 7

Scikit-learnNumPyPandasMatplotlibSeabornStatistical AnalysisPredictive Modeling

Integrations & Messaging · 8

CeleryRabbitMQWebSocketMicroservicesScrapyBeautifulSoupWebhooksTwilio

Education & credentials

EDUCATION

Bachelor of Engineering — Computer Engineering

Aditya Silver Oak Institute of Technology

2018 – 2022

First Class with Distinction

CERTIFICATION

GATE 2021 — Computer Science

IIT Bombay / MHRD

2021

All India Rank 9,081

CERTIFICATION

NPTEL — C Programming

IIT Kharagpur

2020

ELITE Grade

About & contact

The engineer behind the code — working at the intersection of cloud infrastructure and AI.

I'm a senior full stack and data engineer with 4+ years building production-grade systems. My day-to-day is Python backends with Django and FastAPI, cloud infrastructure on AWS and Azure, and generative AI with LangChain, LlamaIndex, and OpenAI.

Especially interested in AI-augmented products and data platforms — the space where a good model meets the infrastructure that keeps it honest. If you're building something like that, I'd like to hear about it.

Ahmedabad, Gujarat, India · IST (UTC +5:30)

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bhargav.py.developer@gmail.com

GitHub /bhargav2800 LinkedIn /in/bhargavpatel2404 X / Twitter @BhargavPyDev Tech blog bhargav-patel-tech.blogspot.com Resume PDF ↗