Advait Bhatt
Bangalore
Summary
Dynamic Senior AI Engineer with proven experience across PwC, EY, and Oracle, driving the design and productionization of cloud-native AI and NLP systems.
Expert in development ofPython-based LLM and Agentic AI solutions
Adept at architecting SaaS-scale AI applications, implementing MLOps pipelines using Docker, FastAPI, and Azure ML, and leading cross-functional data science teams to deliver scalable, reproducible AI solutions
Overview
10
10
years of professional experience
Work History
Senior AI Engineer
PricewaterhouseCoopers (PwC)
Bangalore
11.2021 - Current
- Architected and led the development of a SaaS-based Contract Intelligence Platform, a production-grade AI solution for extracting structured data from unstructured legal and financial contracts. Designed end-to-end Agentic RAG pipelines using LangChain, LangGraph, and Azure OpenAI APIs, containerized via Docker and Azure Functions for hybrid-cloud deployment with observability
- Developed a 4-way Invoice Matching Agent using LangChain, LangGraph, and OpenAI function calling to autonomously reconcile data across Invoices, GRNs, Contracts, and ERP extracts for clients including Royal Enfield and The Walt Disney Company. The agent applied semantic table extraction, context-sensitive matching, and anomaly detection over structured and unstructured documents, enabling near real-time mismatch detection and cost recovery insights.
- Designed and deployed a Procurement Intelligence Agent for the pharma domain, integrating multimodal document processing with GenAI for supplier compliance, rate-card benchmarking, and purchase-order validation. The agent leveraged RAG, vectorized vendor data via FAISS, and LangGraph orchestration for context-aware decision chaining, deployed using FastAPI + Docker Compose with role-based access control on Azure ML endpoints.
Data Scientist -Applied AI
Ernst & Young
Bengaluru
09.2019 - 10.2021
- Architected and deployed a cloud-native cybersecurity data warehouse using AWS Glue, S3, EC2, and Snowflake, integrating data pipelines for real-time anomaly detection. Leveraged open-source frameworks and Power BI to deliver observability dashboards supporting cross-functional security teams.
- Built and deployed a multi-label text classification API service utilizing Transformers and FastAPI, exposed as REST endpoints for integration into R Shiny applications, establishing reusable ML micro-services for business analysts.
- Implemented demand forecasting and yield optimization models for crop-planning projects using Prophet, LSTM, and seasonal ARIMA pipelines. Containerized retraining workflows on AWS Lambda with version-controlled model artifacts in Git.
- Developed NLP-based language translation and data-enrichment modules using Seq2Seq Transformers and spaCy, aligned with open-source principles to promote model transparency and localization for multi-lingual datasets
- Collaborated with engineering and business teams to productionize ML pipelines via CI/CD and IaC (Infrastructure-as-Code), enabling reproducible AI deployments that met enterprise reliability standards.
Application Engineer - RETAIL ANALYTICS
Oracle Retail
Bengaluru
06.2015 - 09.2019
- Engineered open-source–driven machine-learning pipelines for customer segmentation, assortment planning, and inventory optimization using Python (scikit-learn, PyTorch), SQL Server, and Oracle Cloud Infrastructure, aligning with containerized, reproducible ML practices later adopted across the team.
- Built customer segmentation services using clustering algorithms (K-Means, DBSCAN) deployed in micro-container environments with RESTful APIs, enabling real-time personalization and campaign targeting.
- Built assortment planning recommender systems leveraging Collaborative Filtering and Market Basket Analysis (Apriori) to optimize product placement and improve shelf-space utilization across 200+ retail outlets.
- Developed inventory planning and demand forecasting pipelines using ARIMA, Prophet, and Random Forest Regression integrated with Oracle Retail Data Model (RDM) and automated via PL/SQL jobs for weekly replenishment cycles.
Education
PGP - BABI -
Great Lakes Institute of Management
M.Tech - Computer Science
Manipal Institute of Technology
B.Tech - Computer Sicence
SCET
Skills
Core Skills
AI & Machine Learning: LLMs (OpenAI, LangChain, LangGraph), RAG Systems, Deep Learning (PyTorch, TensorFlow), NLP (Hugging Face, spaCy, Transformers)
MLOps & Automation: FastAPI, Docker, CI/CD, Azure ML, AWS S3/Glue/Lambda, Model Monitoring (MLflow, Prometheus)
Data Engineering & Analytics: PySpark, Advanced SQL, Power BI, ETL Pipelines, Snowflake
Open-Source & Cloud-Native Development: Containerized AI Workflows, API-First Design, Hybrid-Cloud Deployments
Domain Expertise: Contract & compliance,Risk Analytics, Cybersecurity Analytics, Retail Forecasting & Optimization, IT and telecommunication
Awards
- Best Paper Award, BAICONF2019, IIM Bangalore, For research on Airbnb NLP Recommendation System, 2019
- Winner, Hackathon, TheMathCompany, 2018
Languages
- English, Proficient (C2)
- Hindi, Proficient (C2)
Languages
English
Proficient
C2
Hindi
Proficient
C2
Timeline
Senior AI Engineer
PricewaterhouseCoopers (PwC)
11.2021 - Current
Data Scientist -Applied AI
Ernst & Young
09.2019 - 10.2021
Application Engineer - RETAIL ANALYTICS
Oracle Retail
06.2015 - 09.2019
PGP - BABI -
Great Lakes Institute of Management
M.Tech - Computer Science
Manipal Institute of Technology
B.Tech - Computer Sicence
SCET