Utkarsh Bajaj

Utkarsh Bajaj

(AI/ML) Business Intelligence Engineer II @ Amazon

About

Most engineers make AI harder than it needs to be. I have shipped multiple production LLM and GenAI systems at Amazon and otherwise. Here I break down what actually works. I have built: - RAG-based LLM production systems using AWS Services - Agentic frameworks for demand forecasting and automated data validation - Data pipelines that handle ingestion, transformation, and quality checks end-to-end - A Unified Data Model that saved thousands of engineering hours across teams Tech I work with: Python, SQL, AWS (Bedrock, Lambda, Step Functions, Redshift, SageMaker) What I post about: - LLM system design and RAG pipelines - GenAI in production: what nobody tells you - Data engineering patterns that scale - Real lessons from building AI at Amazon Outside work: photography and fitness. If you are building with AI or trying to understand it, follow along. #LLMs #GenAI #DataEngineering #MLEngineering #AIEngineering #RAG #AWSBedrock

Country

Canada

City

Greater Toronto Area

Industry

Information Technology & Services

Skill

Front-End Development, Artificial Intelligence (AI), AI Engineering, Data Engineering, Mathematics, Machine Learning, Data Analysis, Data Science, Statistics, C++, R, Microsoft Excel, Communication, Management, Python (Programming Language), Tableau, SAS, Microsoft PowerPoint, SQL, R (Programming Language)

Experience

Amazon

(AI/ML) Business Intelligence Engineer II

Amazon

LinkedIn
2025-8 - Present · 1 yr 2 mos

Toronto, ON

•DataMind: Architected and led the full-stack development of an AWS Bedrock-based GenAI RAG platform, resulting in 51+ monthly active users and 1000+ conversations, projecting 600+ engineering hours saved annually. •Finny (Agentic Forecasting Engine): Established and launched an LLM-powered forecast fine-tuning recommendation engine via a Streamlit web application, reducing manual analysis time by 70% (2,400 annual hours saved).

Amazon

Business Intelligence Engineer II

Amazon

LinkedIn
2024-12 - 2025-8 · 9 mos

United States

•SOP Sherlock (Semantic Search): Designed three-LLM architecture for semantic content similarity detection beyond keyword matching, earning featured poster recognition at Amazon Analyticon conference. •Unified Data Model (UDM): Designed scalable PostgreSQL data model with governance framework (RACI, SOPs) for 11 functions, including validation scripts reducing discrepancies by 80% for onboarded functions. •MLPigeon (MLOps Standardization): Resolved package dependency issues and enhanced SageMaker platform for ML standardization, enabling smoother onboarding and reduced maintenance.

Amazon

Business Intelligence Engineer

Amazon

LinkedIn
2022-7 - 2024-12 · 2 yrs 6 mos

United States

•Developed an automated ensemble forecasting model of investigation task volumes to hire manual investigators for Amazon. Improved forecasting accuracy from 11% in 2022 to 8% in 2023 by statistical analysis and driver identification. •Automated the forecasting process using python scripting enabling the team to generate forecasts within 10 minutes as compared to 5 days. •Created ETL data pipelines and AWS QuickSight dashboards for 5 business functions across the 3 team verticals to allow leaders to get a uniform view of forecast variance. •Devised an app-based headcount optimization solution on Python using Pulp optimizer enabling workforce planning teams to generate optimal headcount instantly.

Advance Auto Parts

Analytics Consultant

Advance Auto Parts

LinkedIn
2022-1 - 2022-7 · 7 mos

United States

•Established a mixed linear integer optimization model across 5450 retail stores in United States utilizing cvxpy package in Python maximizing the profit potential of each store by 11.24% •Performed SKU assortment as a part of prescriptive analysis by assessing shelf space and identifying gaps in supply chain therefore maximizing category and store coverage by 97% on average across all stores •2nd runner up at the 2022 INFORMS Business analytics Conference - Sponsored by SAS (Houston, Texas) •Best paper award at 2022 MWDSI Conference

airtel

Analytics Manager Supply Chain

airtel

LinkedIn
2020-6 - 2021-7 · 1 yr 2 mos

Gurugram

•Led a cross-functional team of 4 members to monitor audit compliances by integrating MySQL and Oracle ERP data monthly thereby produced valuable insights; helped increase the compliance rate from 65% to 85% in Quarter 1 of 2021 •Ensured seamless procurement of these items during covid imposed lockdown; modeled price by ARIMA forecasting saved 6 million USD of CAPEX in that quarter •Developed a metric-based mechanism of ranking supplier performance in VBA and visualized it by QlikView; improved monthly on time delivery by 23% and decreased monthly defect rate by 1.5% for major suppliers

airtel

Senior Executive

airtel

LinkedIn
2019-6 - 2020-6 · 1 yr 1 mo

Gurgaon, India

•Predicted the likelihood of customer churn using logistic regression in the Direct-To-Home business leading to a 2.3% decrease in churn and 26% increase in profitability •Deployed a contract management tool on Excel for quantifying commercial clauses of contracts for all goods and services across Direct-To-Home division, further digitized 92% contracts on central contract repository tool Icertis •Spearheaded audit of processes of third-party logistic providers; validated and optimized the processes saving 3.3 million USD in a single fiscal year

WorldQuant

Websim Research Consultant

WorldQuant

LinkedIn
2018-7 - 2019-5 · 11 mos

Mumbai

•Devised 50+ robust alphas by converting mathematical expressions into Python code to predict performance of financial instruments; achieved returns more than 10% above average •Recommended major trading strategies in US and Asian equity markets by developing algorithmic procedures

airtel

Young Technical Leader (Networks Department)

airtel

LinkedIn
2018-6 - 2018-7 · 2 mos

Gurugram, Haryana, India

•Understood wireless communication systems and different network architectures for 1G,2G,3G,4G, and 5G technology. •Tracked and monitored all National Long distance (NLD) and Point of Interconnect (POI) calls. •Developed a mechanism to report the number of lost calls across India and implemented strategies to reduce them.

Consortium Securities Private Limited

Stock Trading Intern

Consortium Securities Private Limited

LinkedIn
2017-6 - 2017-7 · 2 mos

Rajendra Place, New Delhi

•Understood intricacies of functioning of a Stock Exchanges and a Broking company. •Assisted in trading, settlement of transactions, risk management, client acquisition, and registration.

Education

Purdue University

Purdue University

LinkedIn

Business Analytics and Information Management

2021-8 - 2022-6 · 11 mos
Delhi Technological University (Formerly DCE)

Delhi Technological University (Formerly DCE)

LinkedIn

Electronic and Communications Engineering Technology

2015 - 2019 · 4 yrs
Delhi Public School, Dwarka

Delhi Public School, Dwarka

LinkedIn

Science

2000 - 2015 · 15 yrs

Utkarsh Bajaj's Contact Information

Email

******@***.com

Phone

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