---
title: "Gur Raunaq Singh - Independent AI Engineer | Agentic Systems in Bengaluru | Tal"
description: "Meet Gur Raunaq Singh, AI Engineer | LLMs · RAG · MLOps · Kubernetes | LangChain · LangGraph · Generative AI | 8 Yrs Enterprise AI | Open to Remote based in Bengaluru. AI stack includes claude code, cursor, and langchain. Explore public work links including github and medium."
image: "https://tal.club/meet/gur-raunaq-singh/share-image"
---

# Gur Raunaq Singh on Tal

## Headline

AI Engineer \| LLMs · RAG · MLOps · Kubernetes \| LangChain · LangGraph · Generative AI \| 8 Yrs Enterprise AI \| Open to Remote

## About

Senior AI/ML Engineer with 8\+ years designing and deploying scalable, production\-grade AI systems in enterprise environments\. I specialise in: \- Generative AI & LLMs — RAG architectures, prompt engineering, hallucination reduction, agentic workflows \(LangChain, LangGraph\) \- MLOps & ML Platform — Kubernetes\-native orchestration, MLflow, CI/CD pipelines, model monitoring, distributed training \- Cloud Infrastructure — GCP \(Vertex AI, BigQuery\), AWS, Azure \(AKS\), Terraform, Docker \- Data Engineering — Kafka, PostgreSQL, Redis, FastAPI, Python Some things I've shipped: \- Reduced cloud compute costs by 60% \(\~$240K/year saved\) at a platform serving 100\+ global retailers \- Cut ML deployment time by 60% through standardised CI/CD & model versioning \- Reduced LLM hallucinations by 35% via prompt versioning & evaluation workflows \- Shrunk financial reconciliation cycles by 95% \(2 days → minutes\) for 1,000\+ enterprise customers Currently building AI\-native agentic products at the intersection of ML and autonomous systems\. Open to fully remote roles globally — ML Engineer, AI Engineer, MLOps Engineer, ML Platform Engineer\. 📫 raunaq\.soni@gmail\.com 🔗 github\.com/raunaqness

## Location

Bengaluru

## AI stack

claude code

cursor

langchain

langgraph

langsmith

## Work experience

Independent AI Engineer \| Agentic Systems at Network School, Apr 2026 \- Present · 5 mos, Remote, Building AI\-native products at the intersection of Machine Learning and autonomous agent systems\. As an independent software engineer, I design and ship production\-grade AI applications — focusing on: \- AI Agents and multi\-step agentic workflows \- Applied ML systems beyond prototype stage \- End\-to\-end architecture \(model → orchestration → infra → deployment\) \- Automation systems that reduce operational overhead Currently a Resident at Network School — a frontier community founded by Balaji Srinivasan \(former CTO, Coinbase; former a16z GP\), focused on reimagining startup societies and venture ecosystems\. Actively exploring early\-stage AI opportunities and open to EIR roles or joining as a technical co\-founder / founding engineer in ambitious AI\-first startups\.

Machine Learning Engineer at Aptos Retail, Feb 2023 \- Mar 2026 · 3 yrs 2 mos, Project: Unified Commerce Platform \- Built backend control services for managing ML jobs on Kubernetes, improving flexibility and reliability in job orchestration\. \- Designed cloud\-native data pipelines using Python and BigQuery for efficient and maintainable batch processing\. \- Modernized monolithic systems into modular components to enhance scalability and maintainability\. Tech stack: Python, Django, Google Cloud Platform, SQL, Docker, Kubernetes, Redis, Terraform, BigQuery Project: Internal LLM\-Powered Support Chatbot \- Built an end\-to\-end AI chatbot using large language models to assist users of a retail analytics dashboard\. \- Integrated internal documentation and metadata to provide context\-aware responses using RAG techniques\. \- Deployed the system using MLOps workflows for efficient experimentation and scalability\. Tech stack: Python, FastAPI, LangChain, LangGraph, Vertex AI, VectorDB, Prompt Engineering, Docker, MLOps

Senior Software Engineer at Turing\.com, Jun 2022 \- Feb 2023 · 9 mos, Palo Alto, California, United States, Project: ML Deployment Platform \- Built ML pipelines for data ingestion, training, and automated deployment using Airflow\. \- Implemented standardized MLOps practices to streamline the end\-to\-end ML lifecycle\. Tech stack: Python, Django, Airflow, Google Cloud Platform, Docker, MLOps

Senior Software Engineer at ClickPost, Jul 2018 \- Jun 2022 · 4 yrs, Greater Bengaluru Area, Project: Video Analytics Platform \- Built containerized video processing pipelines for retail environments using edge devices and real\-time analytics\. \- Developed a Kafka\-based architecture for scalable, streaming computer vision workloads\. Tech stack: Python, OpenCV, Kafka, Docker, Computer Vision

Data Scientist at Anheuser\-Busch InBev, Jun 2017 \- Sep 2017 · 4 mos, Bengaluru Area, India, As a Data Science Intern with decent Software Development skills, I worked across multiple teams on the following projects : \- Build a custom Feedback Survey form using Django to collect customer data of their Beer preferences for Sales and Marketing \- Analysed customer purchase data to find key insights on which brands to Marketing based on different Geographies \- Build a web Dashboard with Python and d3\.js for visualising reports data gathered from different teams\. Stack: Python, Django, d3\.js, R, Rstudio\.

## Education

Bachelor of Technology \(B\.Tech\.\), Computer Science, Guru Gobind Singh Indraprastha University

Scaler

## Public links

- github: https://github\.com/raunaqness
- medium: https://medium\.com/@raunaqness

[View the original profile](https://tal.club/meet/gur-raunaq-singh)

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