Headline

AI @ SAP Labs | Ex-Oracle | GenAI, AI Agents, RAG, Conversational AI

About

Machine Learning Engineer with 10+ years of experience building scalable, production-grade ML and AI systems. Strong foundation in classical ML, deep learning, and NLP, with current focus on Generative AI, LLMs, AI agents, and conversational systems. Hands-on experience designing customer support chatbots, RAG pipelines, multi-agent architectures, and tool-augmented LLM workflows, including MCP-based model and tool orchestration. Comfortable owning systems end to end, from data pipelines and model training to inference, evaluation, and deployment. I focus on building AI systems that scale, remain reliable in production, and deliver measurable business impact. Skills: 1. Machine Learning & AI – Generative AI, AI Agents, LLMs, RAG, Classical ML algorithms, Deep Learning, NLP, Langchain, LangGraph, MCP, Pytorch, Keras, Probability and Statistics 2. Languages and Frameworks - Python, Flask, FastAPI, C/C++, SQL, Jenkins, Automation, Pyspark, Hadoop 3. Database - MySQL, Postgres, Teradata 4. Cloud and DevOps - Docker, Kubernetes, Ray, OCI Infrastructure, Git

Location

Kolkata

AI stack

claude code

claude

hugging face

langchain

langgraph

openai

Work experience

Senior AI Developer at SAP, Apr 2026 - Present · 5 mos, Bengaluru

Prinicipal Applied Scientist at Oracle, Jun 2024 - Apr 2026 · 1 yr 11 mos, Bengaluru

Subject Matter Expert at upGrad, Aug 2022 - Jan 2024 · 1 yr 6 mos, Remote, Mentoring Upgrad students to help them transition into data science roles. Responsibilities as a SME includes: - Career Guidance - Technical Assistance - Assignments Evaluation - Webinars

Senior Member Of Technical Staff at Oracle, Jan 2022 - Jun 2024 · 2 yrs 6 mos, Bengaluru, Karnataka, India, Working on upgrading the Customer Service Requests tool with machine learning, NLP and statistical concepts. Domain-Specific SBERT Fine Tuning - The goal is to improve the overall accuracy of clustering and classification models by fine-tuning Sentence-BERT (SBERT) using Masked Language Modeling (MLM) technique to generate high-quality sentence embeddings. Service Requests Topic Prediction - The support team had a requirement to monitor the daily trends of new service requests. To address this, machine learning models were developed to classify service requests into high-priority topics or clusters, as provided by users. Service Requests Topic Clustering - The goal of this project is to enhance customer service by effectively clustering and analyzing service requests. By leveraging Agglomerative Hierarchical clustering, the tool categorizes incoming service requests into distinct clusters. This enables support teams to prioritize and address different types of customer issues, leading to targeted support and product improvement plans.

Python Developer at CES, Apr 2020 - Dec 2021 · 1 yr 9 mos, Hyderabad, Telangana, India

Senior Finance Systems Analyst - Python Developer at Thomson Reuters, Oct 2019 - Apr 2020 · 7 mos, Hyderabad Area, India

Education

Master of Technology - MTech, Data Science, Indian institute of technology Hyderabad

Post Graduate Diploma, Data Science, International Institute of Information Technology Bangalore