Aravind Karteek
Lead Engineer @Pentaleap
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WORK HISTORY
Lead Engineer @Pentaleap
IN
Architected the core B2B platform unifying Demand-Side configuration (Campaigns/AdGroups/Targeting) with Supply-Side inventory management. Built the Admin layer to manage user governance across multi-tenant enterprise accounts, supporting billions of monthly impressions.*: Led the engineering for a data visualization suite featuring + custom charts. Solved critical main-thread blocking issues by offloading complex mathematical aggregations to Web Workers, ensuring zero-latency rendering for large datasets.*(): Built a live simulation environment used by Sales and Product teams to demonstrate real-time ad serving logic to prospects. This reduced technical dependency during sales calls and accelerated client acquisition.*: Manage the frontend squad () across the transition, establishing independent CI/CD pipelines and technical standards for the new entity.
EDUCATION
Andhra University
Master of Business Administration - MBA, Marketing/Marketing Management, General
Velagapudi Ramakrishna Siddhartha Engineering College
Bachelor of Technology (B.Tech.), Electronics and Communication Engineering
Woolf
Master of Science - MS, Computer Science
SKILLS
ABOUT ARAVIND KARTEEK
I sit at the unique intersection of.With 9+ years of engineering leadership (currently at Pentaleap/Crealytics), I bridge the gap between technical architecture and revenue growth. I am currently pursuing concurrent \' and to formalize this expertise:( & ):At, I built the systems that define \"Inventory Availability.\" I architected real-time barcode ingestion and quality control workflows in the warehouse. I understand that you cannot sell what you cannot track.():At Pentaleap, I build the Full-Stack Retail Media Network (RMN) infrastructure. I specialize in connecting the dots between Advertiser Campaign Management and Retailer Inventory Monetization.At, I build the Full-Stack Retail Media Network (RMN) infrastructure. I specialize in connecting the dots between Advertiser Campaign Management and Retailer Inventory Monetization, visualization architectures that help retailers optimize their Media Networks.🤖 ( & ):I actively research and prototype for Retail. Recently, I engineered a taxonomy normalization engine that reduced AI inference costs by 95% using In-Memory Vector Search. I focus on how to make GenAI profitable, not just functional:I don\'t just manage timelines. I de-risk architecture. Whether it\'s replacing expensive licensed tools with Open Source (saving Tata Sky Broadband budgets) or reducing API latency for AdTech, I focus on scalable, profitable engineering: Node.js, React, RAG, Vector DBs, Kafka, Shopify Ecosystem.
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