---
title: "Shubham Naik - Senior AI Engineer in Bengaluru | Tal"
description: "Meet Shubham Naik, Senior AI Engineer @ Toast ✦ Previously @SAP Labs · @Accenture ✦ Building AI Systems that survive production, not just demos ✦ Generative AI · Agentic AI · Machine Learning · Artificial Intelligence based in Bengaluru. AI stack includes anthropic apis, claude code, and deepseek...."
image: "https://tal.club/meet/shubham-naik/share-image"
---

# Shubham Naik on Tal

## Headline

Senior AI Engineer @ Toast ✦ Previously @SAP Labs · @Accenture ✦ Building AI Systems that survive production, not just demos ✦ Generative AI · Agentic AI · Machine Learning · Artificial Intelligence

## About

Most AI demos work\. Most AI in production doesn't\. I work on that gap\. I'm a Senior AI Engineer on the Ads & Insights team at Toast, building agentic and LLM systems that have to survive real traffic — where "it worked in the notebook" is the start of the problem, not the end\. Before Toast, I helped build SAP's Joule copilot, where I co\-invented a patent\-pending AST\-based code\-context retrieval framework: deterministic code understanding for AI agents that beat semantic search on completeness \(95% vs 65%\) while cutting token cost per call by \~60%\. Earlier, at Accenture, I shipped RAG systems and GenAI tooling across enterprise clients\. The foundation under all of it is classical ML — I was training and shipping models before "GenAI" was even a category\. That's exactly why I can tell demo\-ware from something that'll actually hold up in production\. What I actually obsess over — the stuff that decides whether an agent is a product or a retry script: → Retrieval quality over bigger models → Eval harnesses and benchmarking → Token economics → State machines over "autonomous" loops I write about the real version of building with LLMs here — what works, what's hype, and what it actually costs\. If that's your kind of thing, follow along\. Stack I live in: Agentic AI · LLMOps · RAG · Python · AWS · Classical ML · evaluation & benchmarking\. Building something in this space? Let's talk\. Portfolio's in my Featured\. 👇

## Location

Bengaluru

## AI stack

anthropic apis

claude code

deepseek

langfuse

langgraph

huggingface

## Work experience

Senior AI Engineer at Toast, May 2026 \- Present · 5 mos, Bengaluru, • Building AdTech Intelligence • Leading AI feature strategy for the Ads and Insights products\.

AI Engineer II at SAP, Mar 2025 \- May 2026 · 1 yr 3 mos, Bengaluru, Building SAP Joule • Creating SAP’s flagship agentic solution, working as a copilot embedded in the SAP product ecosystem, providing seamless connectivity and a unified experience across products\. • Co\-invented a patent\-pending AST\-based code context retrieval framework enabling AI agents to deterministically extract code context and dependencies, replacing grep\-based pattern matching and semantic search\. Showing 25% first\-pass code accuracy lift, 60% token consumption reduction per agent call, 95% retrieval completeness vs\. 65% semantic baseline\. Preceded similar capabilities in Copilot Workspace by 6\+ months\. • Worked on Joule for Developer \(J4D\) intended for accelerating migration of legacy ECC code to the S/4 Hana cloud environment by implementing an end\-to\-end code generation pipeline, reducing migration timelines by 35% • Fine\-tuned open\-source foundation models for specific use cases, including text\-to\-code and code\-to\-code use cases\. • Created a benchmarking framework for code quality assessment with dynamic unit tests, syntax checks and LLM\-as\-a\-judge manual evaluation dependency, improving feature shipping time by 15%

Machine Learning Engineer at Accenture, Sep 2023 \- Mar 2025 · 1 yr 7 mos, Bengaluru, • Developed a procedure to transform the existing content of an enterprise\-level website into an indexed vector database, creating a knowledge base for a RAG\-enabled chatbot that served as a quick search tool and cut down search time for users by 15%, significantly boosting user retention\. • Designed and implemented a content approval system for a pharmaceutical client, enabling regulatory and legal approvers to evaluate and approve campaign content being published on the website\. Reduced approval time per page from 4 hours to 2\.5 hours, directly reducing go\-live time and marketing campaign timelines\. • Built a risk assessment model for predicting at\-risk deliverables, increasing time\-bound objective delivery by 25%, especially in remote working projects\. • Collaborated with over 12 projects to create standardised runbooks for the induction of generative AI tools, significantly enhancing work efficiency while ensuring data integrity and compliance\. • Deployed generative AI POCs in working with large language models such as Llama\-2/3, Mistral, and GPT\-3\.5/4, augmenting with a vector database with frameworks like LangChain and Streamlit

Associate Software Engineer at Accenture, Jun 2021 \- Sep 2023 · 2 yrs 4 mos, Bengaluru, • Built a content management system with multilingual support for no\-code content authoring, targeting campaigns, and executing workflows with custom components\. • Audited and refactored the existing application for bottleneck fixes that would yield maximum improvement, resulting in an increased page performance score \(Lighthouse\) by 135% with a 30% tech debt reduction\. • Migrated rich media hosting Scene7 to enhance media processing capabilities, accelerate image loading, and remove dependency on device\-specific image renditions, resulting in a 50% drop in the size of media\-heavy pages • Developed a server cleanup utility for clearing servers of long\-dormant pages and media to save space and keep servers lightweight, leading to a 15% server bloat reduction\. • Engineered an ITSM management framework, revamping ITSM handling procedures across the project, resulting in a 60% drop in incident/service request response time and over a 90% drop in active incidents/tickets\.

Machine Learning Instructor at Edurific, Jul 2020 \- Mar 2021 · 9 mos, Mumbai, Maharashtra, India, ● Worked as an AI/ML Instructor and implemented end\-to\-end Machine Learning projects for integrating into courses\. ● Libraries worked with: Scikit Learn, TensorFlow, NumPy & Pandas, Keras, Flask, Streamlit\. ● Project Worked on: Time series analysis of Airways miles\. Face mask detection module\. ● Delivered sessions on concepts in ML application development along with programming requisites\. ● Built Dialogflow Chatbot for streamlining content delivery\. ● The projects created impacted over 700 students\.

## Education

Bachelor of Engineering \- BE, Computer Engineering, K\. J\. Somaiya Institute of Technology

Junior College, Dadasaheb Tirodkar Jr\. College

## Public links

- github: https://github\.com/naikshubham14
- shubhamnaik\.vercel\.app: https://shubhamnaik\.vercel\.app/

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

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