Sidharth R.
Available for new opportunities

Hello, my name is
Sidharth R.

Lead Software Engineer @ Persistent Systems | Data Engineering & GenAI Expert

Specializing in Generative AI for healthcare. Leveraging Vertex AI, Vespa AI, and AWS to build scalable AI solutions. Ex IBM | MS in ML & AI @ LJMU '26 | PGD @ IIIT-B '25 | B.E. @ CU '20

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Sidharth R.

About me

I engineer applications using data intelligence.

6+
Years of Experience
GenAI
& Data Engineering

Sidharth R. is a Lead Software Engineer at Persistent Systems with over 6 years of experience, specializing in Generative AI applications within the healthcare domain. Leveraging tools like Vertex AI and AWS, he drives enterprise-grade production deployments that deliver real-world impact.

From architecting scalable data solutions with Databricks, Unity Catalog, and Medallion architectures to designing high-performance Distributed Search Orchestration and Agentic AI workflows, Sidharth R. brings comprehensive expertise across the entire data and AI lifecycle. His strong foundation was honed at IBM, focusing on model development, optimization, and advanced analytics using Python and PyTorch.

Passionate about the transformative potential of AI, he is continuously enhancing his expertise through an MS in Machine Learning and AI from Liverpool John Moores University and a Postgraduate Diploma from IIIT-Bangalore.

Sidharth R. is a certified expert in Azure AI, Data Science, and GenAI (including Gemini and Imagen). His technical arsenal features advanced methodologies like Machine Learning (LightGBM, ONNX), Retrieval-Augmented Generation (RAG), LLM fine-tuning, and Agentic AI, backed by a history of research publications, patents, and enterprise-scale deployments.

What I do

From understanding your requirements, designing a blueprint and delivering the final product, I do everything that falls in between these lines.

Agentic AI

Building advanced agentic AI applications to automate complex tasks and enhance decision-making processes.

Data Science

Crafting insights from data, deploying machine learning models, and diving into computer vision—bridging the gap between raw data and meaningful solutions.

Web Development

Elevating digital presence with WordPress mastery—customized designs, seamless WooCommerce, Shopify integration, and dynamic layouts for a captivating online experience.

Portfolio & Works

A showcase of my research publications, patents, and engineering projects across multiple domains including Healthcare, Supply Chain, and Finance.

2+Publications
1+Patents
8+Projects
...& counting
Research Paper

Strategic: Risk, Return and Technical Analysis of Stock Prices

Quantitative Finance, Predictive Modeling & ML

This research addresses the high volatility and complexity of stock market movements by synthesizing fundamental indicators with technical analysis. The paper introduces and implements a novel machine learning framework engineered specifically to filter market "noise" and predict asset price trajectories under volatile conditions, offering a robust empirical model for algorithmic decision-making.

SSRN Publication
Patent

Desmogging Framework for Intelligent Transport

Computer Vision & Infrastructure

A proprietary hardware-and-software-aligned framework designed to perform real-time, low-latency "desmogging" (dehazing) on live visual data streams. Ensures operational safety of autonomous transit networks in polluted urban ecosystems.

Patent IN 201911036469
Research Paper

Adaptive Prompt Engineering Strategies for GenAI in Finance

Generative AI Architecture, LLMs, & Financial NLP

Tackles critical bottlenecks of deploying LLMs within highly precise, domain-specific environments like finance. The methodology centers on designing dynamic orchestration techniques like Tree-of-Thought (ToT) and Chain-of-Thought (CoT) to guide an LLM to self-evaluate, deliberate on intermediate financial metrics, and correct its course mid-generation.

Research Publication
Enterprise Project

GenAI Solutions for Supply Chain & Business Intelligence

Azure OpenAI, RAG, LLM Fine-Tuning (PEFT/LoRA) & Predictive Analytics

Developed Generative AI models using Azure OpenAI and RAG to optimize supply chain intelligence. Built an AI CRM bot using LoRA reducing response times by 27%, and a LangChain SQL Query Generator improving performance by 35%. Integrated predictive time-series models to reduce forecasting inefficiencies by 20%.

Industry Deployment
Enterprise Project

GenAI-Powered Supply Chain Optimization Bot

Conversational AI, Demand Forecasting & Voice Assistants

Engineered an AI-powered chatbot and voice assistant for real-time inventory tracking, demand forecasting, and vendor management. The voice bot enables hands-free operational updates through natural language commands, leveraging Azure AI Speech Services, STT, and Power BI embedded APIs.

Enterprise Solution
Enterprise Project

Conversational AI for SQL Queries Bot

Azure OpenAI, LangChain, RAG & Vector Databases

Developed an AI-powered query generator enabling users to retrieve database insights via natural language. Built with Azure OpenAI, LangChain, and RAG architectures integrated with Qdrant vector databases and SQLAlchemy, significantly improving dynamic database query resolution by 35%.

Enterprise Solution
Enterprise Project

Data Engineering Library & ETL Pipelines

PySpark, Databricks, Medallion Architecture & Delta Lake

Developed a reusable Python library and ETL suite for large-scale healthcare data processing on cloud-based Databricks clusters. Implemented a full Medallion architecture for patient and provider data ingestion from AWS S3, utilizing PySpark for complex transformations. Enabled advanced TF-IDF scoring and geocoding enrichment, processing millions of records for real-time healthcare search indexing via MongoDB Atlas.

Healthcare Data Platform
Enterprise Project

Enterprise MongoDB Data Platform

FastAPI, MongoDB Atlas, NLP (Transformers) & Argo Workflows

Architected a scalable MongoDB data platform serving diverse knowledge bases with a strong emphasis on healthcare data structures. Implemented multi-step Argo Workflow pipelines for automated data ingestion. Built FastAPI-based REST services and integrated Sentence Transformers for semantic embedding generation enabling intelligent provider search, processing millions of complex medical documents.

Healthcare & Enterprise Solutions
Enterprise Project

Search Orchestration API & Service Aggregation Library

FastAPI, Async HTTP, OpenTelemetry, Kubernetes & Distributed Systems

Architected a search orchestration API and reusable library to multiplex requests across diverse search backends and consolidate results. Leveraging an abstract base class pattern, it enables plug-and-play integration for providers like Vespa and MongoDB Search. Implemented high-performance async communication via httpx, OpenTelemetry distributed tracing, and Pydantic for type-safe DTOs. Containerized and deployed on Kubernetes to improve response times and centralize search routing.

Unified Search Architecture
Enterprise Project

ML-Powered Provider Search with Semantic Ranking

MongoDB Atlas Vector Search, LightGBM, ONNX & Databricks

Architected an ML-powered healthcare provider search system featuring multi-phase ranking: MongoDB Atlas Vector Search for candidate retrieval and LightGBM for personalized re-ranking. Engineered 384-dimensional ONNX sentence transformer embeddings for semantic encoding and built full-load Databricks ingestion pipelines. Achieved sub-millisecond query performance via denormalized schema design, deployed seamlessly on Kubernetes.

Healthcare Search Architecture
Enterprise Project

AI-Powered Search Micro-Frontend

React 18, TypeScript, Module Federation, MUI & Real-Time AI

Developed a React-based micro-frontend for healthcare provider search, featuring an AI-powered conversational interface with real-time streaming. Built interactive management UIs with dynamic filtering, geolocation proximity search, and comprehensive export functionalities. Configured Module Federation via Rsbuild for seamless host integration as an independently deployable unit, ensuring component reliability across breakpoints with Jest.

Frontend Architecture

Skills

Technical proficiency across the modern data and AI stack.

Generative & Agentic AI

Azure OpenAI, RAG, LoRA, Agentic AI, LLMs

95%

AI Models & Frameworks

Claude, Gemini, Llama, LangChain, Sentence Transformers, ONNX, LightGBM

90%

Data Engineering & Processing

PySpark, Databricks, Medallion Architecture, Delta Lake, Argo Workflows

95%

Backend & MLOps

FastAPI, Python, OpenTelemetry, Pydantic, Async HTTP, Docker, Kubernetes

90%

Databases & Search

MongoDB Atlas (Vector Search), Qdrant, Vespa, SQL, Elasticsearch

90%

Frontend & UI Architecture

React 18, TypeScript, Module Federation (Micro-Frontends), MUI, Tailwind CSS, Jest

85%

My Experience

Data Engineer / Lead Software Engineer

April 2025 - Present
Persistent Systems • Gurugram, India

Designed scalable data solutions and ETL/ELT pipelines using Databricks, Unity Catalog, Delta Lake, and Medallion Architecture. Built unified distributed search orchestration APIs with FastAPI, OpenTelemetry, and Kubernetes. Led backend engineering with MongoDB Atlas (Vector Search) and engineered React-based AI Micro-Frontends. Integrated Agentic AI, RAG frameworks, and advanced Prompt Engineering to build transformative Generative AI deployments.

Application Developer & Associate System Engineer

Jan 2021 - April 2025
IBM • Gurugram / Bengaluru, India

Focused on machine learning model development, optimization, and deployment using Python and TensorFlow. Facilitated end-to-end ML lifecycles, structured robust data environments, and mentored team members.

Software Development Engineer

Jun 2020 - Dec 2020
AXL Electric Vehicles • Toronto, Canada (Remote)

Led the development of a sentiment analysis system for tweets, achieving 80% accuracy. Conducted in-depth research and architected features for a secure, end-to-end encrypted messaging application.

Software Developer

Jan 2019 - Mar 2019
Tecnovix - Soluções Inteligentes • São Paulo, Brazil (Remote)

Implemented data pre-processing techniques and developed effective Machine Learning models using Python. Promoted to project mentor to guide colleagues in ML implementations.

My Education

Master of Science - MS, Machine Learning and AI Articulation

May 2025 – Apr 2026
Liverpool John Moores University

Executive Postgraduate Diploma, Machine Learning & Artificial Intelligence

Mar 2024 – Apr 2025
International Institute of Information Technology Bangalore

Bachelor of Engineering (B.E.), Computer Science

Aug 2016 – May 2020
CHANDIGARH UNIVERSITY

Higher Secondary Education

2002 – 2015
Sunbeam English School, Bhagwanpur