Prachi  ·  Python / GenAI Engineer  ·  4.5+ yrs

Mid-Level
4.5+ years experienceremote
Available within 48 hrs

About Prachi

Data scientist + Generative AI engineer with delivery across LLM-powered document classification, RAG pharma chatbot on GPT-4 + ChromaDB, ML return-volume prediction for logistics, and e-commerce LLM customer support chatbot with intent + NER + sentiment.

4.5+ years of commercial experience in

AI / ML PlatformLogistics & Supply Chain

Skills(48)

GPT-4LangChainAWSPythonFastAPIRAGchroma dbSQLDockerDjangoFlaskOpenAI APIsAzure OpenAIHugging FacePrompt EngineeringLLM Fine-tuningFAISSLangGraphAWS BedrockS3RDSEC2LambdaECRSagemakerGitHub ActionsGitLab CIECSTransformersNLTKSpaCyscikit-learnKerasTensorFlowPower BIPostgreSQLXGBoostApp RunnerTextractAzure AI StudioLabel StudioSvelte JSAWS TextractChromaDBOpenAIAWS ECSAWS LambdaAWS App Runner

Why hire Prachi?

GenAI engineer trackRAG + LLM production systemsMulti-domain ML delivery

Built LLM-powered document classification + entity extraction pipeline for enterprise documents.

Delivered AI-powered pharma chatbot on GPT-4 + RAG + ChromaDB.

Shipped Return Volume Prediction ML solution for a logistics company.

Built e-commerce LLM chatbot with intent detection, NER, sentiment + feedback loops.

Hands-on GenAI / LLM engineering

RAG + intent + NER + sentiment full-stack ML

Multiple production LLM systems

Project highlights(4)

N23 — Document Classification using LLMs – Generative AI Engineer

  • LLM-powered pipeline for document classification and entity extraction in enterprise documents — combining GPT-4 with NER models for intelligent classification and tagging.
  • Designed and implemented classification + NER pipeline using GPT-4 and custom-trained models.
  • Integrated Label Studio for human-in-the-loop feedback.
  • Used AWS Textract for OCR-based content extraction.
  • Deployed models via SageMaker, triggered workflows with Lambda, exposed APIs via FastAPI.
  • Packaged services via Docker and managed with ECS.
  • Maintained CI/CD pipelines via GitHub Actions.
  • Tuned prompt templates to improve classification accuracy and reduce LLM token consumption.
GPT-4FastAPIAWS TextractSageMakerLambdaDockerECSGitHub ActionsLabel Studio

Key outcomes:

  • Reduced LLM token consumption + improved classification accuracy via prompt-template tuning.

  • Built human-in-the-loop pipeline with Label Studio + GPT-4 + custom NER models.

AI-Powered Pharma Chatbot – Generative AI Engineer

  • Generative AI chatbot answering medical and research-based queries using GPT-4 + RAG with ChromaDB. Hosted on AWS ECS + S3.
  • Implemented RAG architecture using LangChain for context-rich responses.
  • Embedded pharma documents using OpenAI embeddings in ChromaDB.
  • Developed FastAPI microservices behind Docker containers.
  • Managed vector indexing and retrieval workflows.
  • Deployed backend on AWS ECS integrated with S3, RDS, ECR.
  • Created prompt templates and adjusted token management to control API costs.
  • Collaborated with Svelte JS frontend team for API consumption.
  • Implemented logging, monitoring and access control for LLM endpoints.
GPT-4LangChainChromaDBOpenAIFastAPIDockerAWS ECSS3RDSECR

Key outcomes:

  • Built RAG-based pharma chatbot with ChromaDB vector store and AWS ECS deployment.

  • Optimised prompt templates to control API costs.

Return Volume Prediction (RVP) – Data Scientist

  • AI solution to forecast return volumes of parcels for a logistics company using ML, integrated with dashboards and APIs.
  • Engineered time-series ML models using scikit-learn and XGBoost.
  • Built FastAPI APIs to expose predictions to business dashboards.
  • Integrated Power BI for visualising return volume trends.
  • Processed structured data from PostgreSQL and S3.
  • Deployed services using Docker and automated workflows with GitHub Actions.
  • Managed data ingestion pipelines using AWS Lambda.
  • Performed hyperparameter tuning and model evaluation on validation data.
scikit-learnXGBoostFastAPIPower BIPostgreSQLS3AWS LambdaDockerGitHub Actions

Key outcomes:

  • Engineered scikit-learn + XGBoost time-series models for parcel return-volume prediction.

  • Integrated Power BI for stakeholder-facing return-volume trend visualisation.

E-Commerce LLM Chatbot – AI Engineer

E-commerce LLM chatbot with intent detection, NER, sentiment and feedback loops.

LangChainGPT-4FAISSFastAPIDockerAWS App RunnerECRPostgreSQL

Key outcomes:

  • Built multi-turn e-commerce LLM chatbot with FAISS semantic search and feedback-loop fine-tuning.

Industry experience

AI / ML Platform

4 projects
  • •N23 — Document Classification using LLMs— Generative AI EngineerGPT-4 · FastAPI · AWS Textract · SageMaker +5
  • •AI-Powered Pharma Chatbot— Generative AI EngineerGPT-4 · LangChain · ChromaDB · OpenAI +6
  • •Return Volume Prediction (RVP)— Data Scientistscikit-learn · XGBoost · FastAPI · Power BI +5
  • •E-Commerce LLM Chatbot— AI EngineerLangChain · GPT-4 · FAISS · FastAPI +4

Logistics & Supply Chain

1 project
  • •Return Volume Prediction (RVP)— Data Scientistscikit-learn · XGBoost · FastAPI · Power BI +5

Ready to work with Prachi?

Schedule an interview and onboard within 48 hours. No long hiring cycles.

At a Glance

Experience4.5+ years
Work moderemote
Starting from₹1.6 L/mo
Direct hirePossible
Start within48 hours
From₹1.6 L/ month

Single contract. No agency markup confusion.

Typically responds within 4 business hours.

5-day replacement guarantee
48-hour onboarding, single invoice
Direct chat — no recruiter middleman
VerifiedVetted by Witarist
Technical skills assessed & verified
Background & identity checked
English communication verified
Ready to onboard in 48 hours

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Prachi

Data Scientist