---
title: "Ankur Dhuriya - Senior Data Scientist in New Delhi | Tal"
description: "Meet Ankur Dhuriya, AI Engineer @ ThoughtWorks | Customizing LLMs for Life Sciences & Procurement | Fine-tuning • RAG • RLHF | AI R&D | MLOps based in New Delhi. AI stack includes antigravity, opencode, and claudecode. Explore public work links including github."
image: "https://tal.club/meet/ankur-dhuriya/share-image"
---

# Ankur Dhuriya on Tal

## Headline

AI Engineer @ ThoughtWorks \| Customizing LLMs for Life Sciences & Procurement \| Fine\-tuning • RAG • RLHF \| AI R&D \| MLOps

## About

Senior Applied AI Engineer with 6\+ years of experience architecting enterprise\-grade GenAI, RAG, and agentic applications\. Expert in designing multi\-step agent workflows using LangChain, LangGraph, and LlamaIndex, and implementing MCP\-based context sharing for seamless enterprise interoperability\. Proven track record in building robust ETL pipelines for document ingestion, developing secure microservices/APIs, and establishing comprehensive observability and evaluation frameworks\. Proficient in Python best practices, CI/CD, and deploying scalable solutions on AWS Bedrock, Azure OpenAI, and open\-source LLMs \(LLaMA, Qwen\)\.

## Location

New Delhi

## AI stack

antigravity

opencode

claudecode

## Work experience

Senior Data Scientist at Thoughtworks, Jul 2025 \- Present · 1 yr 2 mos, Gurugram, Architected and deployed a compliant, production\-grade RAG chatbot for LifeScience Preclinical Safety team using AWS Bedrock, Claude Sonnet, and LangGraph; established end\-to\-end MLOps pipelines via GitHub Actions and Kubernetes with Weights & Biases for observability, implemented strict ALM protocols through SonarQube security gating, and developed a custom “Golden Dataset” evaluation framework that achieved 95% accuracy in a highly regulated pharmaceutical environment while streamlining access to critical research documentation\. Agentic AI & MCP Integration: Architected a unified Copilot assistant using LangGraph and LlamaIndex, implementing MCP\-based context sharing to enable seamless A2A integrations across Jira, Confluence, GitHub, and Databricks for real\-time enterprise knowledge retrieval\. Observability & Evaluation Frameworks: Established robust observability using LangSmith and DeepEval, implementing logging, tracing, and prompt tracking to monitor quality metrics\. Achieved 94% accuracy in Biomedical QA via a self\-reflective reasoning framework \(Qwen3/LLaMA\) with structured XML outputs\. Performance Optimization: Designed a semantic caching layer with Redis, reducing latency from 6s to <800ms and cutting inference costs by 50% for 10K\+ daily queries\. Integrated Amazon Bedrock and Azure OpenAI to optimize model selection for cost/performance trade\-offs\. API & Microservices Development: Developed secure, scalable FastAPI microservices for AI inference, adhering to high\-quality Python coding standards \(modularity, testing, documentation\) and ensuring seamless integration with frontend interfaces\.

Senior Data Scientist at GEP Worldwide, Dec 2024 \- Jul 2025 · 8 mos, Hyderabad, ETL & Document Pipelines: Built end\-to\-end ETL pipelines for document ingestion, parsing \(OCR/IDP\), and enrichment, processing 50K\+ invoices/month\. Implemented hybrid retrieval \(BM25 \+ embeddings\) over SQL/NoSQL databases and Vector Stores \(Pinecone\) for accurate RAG\-based insights\. RAG & LLM Integration: Engineered a spend analytics NLQ chatbot using LangChain and OpenAI/Claude models, achieving 92% answer relevance\. Collaborated with SMEs to translate business needs into technical solutions, reducing AP cycle time by 35%\. CI/CD & Productionization: Implemented robust CI/CD pipelines using Azure DevOps for automated testing and deployment of AI models to Azure Kubernetes Service \(AKS\), ensuring reliable production releases and version control for prompts and code\. Security & Governance: Integrated custom guardrails for PII detection and prompt injection filtering, ensuring secure and compliant AI interactions in enterprise environments\.

Data Scientist at Builder\.ai, Dec 2022 \- Dec 2024 · 2 yrs 1 mo, Gurugram, time by 70% \(45min → 12min\) with 94% syntactic correctness\. Microservices & API Design: Designed and maintained robust FastAPI microservices for mul\- tilingual transcription summarization, processing 10K\+ calls/day across 8 languages\. Ensured high\-quality Python code with comprehensive unit tests and modular design\. Observability & Monitoring: Implemented comprehensive logging and tracing for agent runs, enabling rapid debugging and performance tuning\. Automated evaluation pipelines tracked halluci\- nation rates and safety scores \(99\.2%\), ensuring system reliability\. Cloud Deployment: Deployed scalable AI workloads on AWS SageMaker and Bedrock, utilizing Docker and Kubernetes for container orchestration and auto\-scaling to handle peak traffic efficiently\.

Data Scientist at Thoughtworks, Sep 2020 \- Dec 2022 · 2 yrs 4 mos, Pune Division, Spearheaded the delivery of ASR systems for 18 Indic languages using PyTorch\-based Wav2Vec 2\.0, outperforming competitors by 15\-20% WER through custom lexicon integration and data enrichment pipelines\. Built TTS pipelines for 8 languages using GlowTTS and HiFi\-GAN, achieving a 4\.2 MOS score in production\. Implemented BERT\-based Inverse Text Normalization, improving transcription accuracy by 12% through robust post\-processing techniques\.

Data Science Intern at Thoughtworks, Feb 2020 \- Aug 2020 · 7 mos, Gurugram

## Education

Master of Science \- MS, Machine Learning & AI, Liverpool John Moores University

Bachelor of Technology \- BTech, Computer Science, DIT University

## Public links

- github: https://github\.com/ankurdhuriya

[View the original profile](https://tal.club/meet/ankur-dhuriya)

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