Ranny N.

Ranny N.

India
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About Me

Ranny is a high-impact AI Software Developer and Backend Engineer with a proven track record of building scalable, event-driven architectures and production-grade Generative AI solutions. With deep expertise in the Python ecosystem and AWS infrastructure, she specializes in bridging the gap between complex machine learning models and robust, high-performance backend systems. Her core technical strengths include advanced GenAI development, where she is highly proficient in building modular RAG pipelines and multi-agent systems using CrewAI, alongside orchestrating various LLMs for specialized enterprise use cases.<br><br>In the realm of event-driven architecture, Ranny has extensive experience implementing real-time streaming services and microservices communication using Apache Kafka. She is widely recognized for her engineering rigor and has successfully reduced API latency by 40% through the implementation of advanced LRU caching and optimized query structures. Her technical versatility extends to cloud operations and DevOps, where she skillfully manages Docker-based containerization and complex cloud workflows using AWS Lambda, SQS, and integrated CI/CD pipelines.<br><br>As a proactive problem-solver who thrives in agile environments, Ranny excels at architecting secure API gateways with FastAPI and fine-tuning retrieval mechanisms to ensure better grounding and accuracy. Throughout her career, she has remained focused on delivering efficient, high-availability systems that drive measurable business value and operational excellence.

AI, ML & LLM

Machine Learning FAISS LangChain Langsmith AWS Bedrock

Backend

Python

Database

MongoDB

DevOps

Docker AWS Codepipeline AWS EC2 AWS SQS

Other

Apache Kafka CrewAl Tmux Nginx SQS FFMPEG Whisper spacy Google Dialogflow Tableau Power BI EDA Feature Engineering Sentiment Analysis Tkinter Postgres Typescript NestJS Data Analysis Data Visualization Feature Engineering Statistical Analysis Huggingface Prisma Keras Lambda Functions Predictive Modeling Linux Gradio Elasticsearch

Work history

Radiansys
Al Software Developer
2024 - 2026 (2 years)
Remote

  • Established real-time event-driven communication across microservices using Apache Kafka, enabling live notifications and efficient data propagation.

  • Implemented a modular RAG pipeline integrated with PostgreSQL and various LLM tools for enhanced inference monitoring and multi-LLM support.

  • Integrated Azure Al Foundry via SDKs and implemented LRU caching to optimize backend processing and reduce infrastructure utilization.

Apache Kafka PostgreSQLLangChain LlamaParser Llamalndex Langsmith AWS Bedrock CrewAl DockerTmux NginxLambdaSQS Twilio APIs Zoom C++ SDK Webex SDK FFMPEGWhisperMongoDB
Factacy
Al Engineer
2023 - 2024 (1 year)
Remote

  • Worked with advanced LLMs (LLama2, Mistral 7b), focusing on inference performance and developed a RAG pipeline using Langchain, FAISS, HuggingFace, and Knowledge Graphs for improved data retrieval.

  • Fine-tuned a custom NER model with SpaCy, reducing inference time while maintaining accuracy, deployed on Azure.

  • Developed a multi-class classification system using Multinomial Naive Bayes, and customized a dataset using ML techniques and built a system supporting multiple LLM interfaces.

Llama2 Mistral 7b LangChain FAISS Huggingface Knowledge Graphs spacyAzure Multinomial Naive Bayes
Edupeer
Associate Data Scientist
2022 - 2022
Remote

  • Developed chatbots using Rasa and Google DialogFlow, increasing user interaction with the business by 30% and improving experience.

  • Analyzed PostgreSQL data to deliver actionable business insights.

  • Created impactful dashboards in Tableau and Power BI using EDA and feature engineering.

Rasa Google DialogflowPostgreSQLTableauPower BI EDA Feature Engineering
Defence Research and Development Organisation
Research and Development Intern
2022 - 2022
Remote

  • Developed scalable Multilevel Models for analyzing multi-stage data and extracting insights from large numerical datasets.

  • Built a PDF text extraction and sentiment analysis model, improving processing accuracy and efficiency.

  • Designed user-friendly GUIs with Tkinter and packaged Python scripts into .exe files for easy deployment.

Multilevel Models PDF text extraction Sentiment Analysis Tkinter Python

Education

Education
Bachelor of Technology
Dronacharya College of Engineering
2018 - 2022 (4 years)