Los Altos, California, United States
Engineering leader with an extensive experience in building high-performance teams and start-ups. Expertise in building large-scale data and machine learning platforms and full-stack products.
As Head of Engineering at Apollo, I lead all engineering across the organization, a global team of 200+ spanning Americas, Europe, and Asia. At the intersection of AI, organizational scale, and platform foundations, my focus is on building Apollo a pioneer of the AI-agentic era for GTM.
As VP of Engineering at Apollo, I lead Machine Learning, Data, and several product verticals that power the world’s fastest-growing GTM platform. I oversee a global organization of ~100 engineers and builders across APAC, North America, and Europe. I’m driving Apollo’s transition into an AI-native company, reimagining how we build, operate, and scale products. Through broad adoption of AI tooling (for coding, code reviews, incident management, testing, etc.) and workflows, we’ve transformed engineering productivity and accelerated innovation across the org. I also lead the development of Apollo’s AI Assistant, one of the most advanced AI agent platforms in the GTM space. With agents for Prospecting, Sequences, Workflows, Analytics, and Enrichment already live, and next-generation capabilities like Agentic Workflows and Agent Builder underway, we are redefining how modern teams go to market. At the intersection of AI, product, and organizational scale, my focus is on shaping Apollo into not just a category leader, but a pioneer of the AI-agentic era for GTM.
Apollo.io is a leading provider of sales intelligence products. Backed by Sequoia Capital and Bain Capital Ventures, it became the first unicorn in the sales domain in 2023 with a valuation of $1.6B. I lead all things data and machine learning at Apollo, including all full-stack verticals that utilize data and ML. My org has 10+ teams led by managers, senior managers, staff engineers, and principal engineers, with a total size of 75+ people. These teams are spread across 5+ countries and operate in a fully remote setting. My org’s horizontal charter includes Data Platform, Data Engineering, ML Platform (including LLM Ops), ML Engineering, and Search Relevance. My vertical charter includes Apollo’s foundational products like Data offerings, Prospecting (search engine), Sales Engagement, and Plays. I am also leading Apollo’s Engineering Hiring program and have successfully hired more than 150 engineers on the Engineering team, a growth of ~700% since Jan 2022.
Storepath helped eCommerce sellers in expanding their business to multiple channels and countries. Our AI and data-driven approach allowed us to automate most aspects of the eCommerce business so sellers, brands, and merchants can focus on building and improving their products. Storepath raised $4M in funding from Fika Ventures, Neo (Ali Partovi's VC firm), Act One Ventures, and other angels. I led the technology (and whatever else that came my way) at Storepath. We launched approximately one big product per month and experimented rapidly to gather quick feedback from customers. Some of our notable products were: AI-powered seller tools (Copy Creator, Keyword Researcher, Listing Optimizer, Merchant Portal), an on-demand marketplace (webapp and mobile app) to connect eCommerce brands with freelancers, a Shopify app for automated Copy Creation using OpenAI's GPT-3 models, and an ML model to predict the valuation of eCommerce businesses.
Led multiple full-stack teams and initiatives, launching multiple highly impactful projects for student Admissions and Learning. -- Introduced and set up various engineering processes like Scrum, Oncall, and Engineering Onboarding while improved many others like Hiring, Roadmap, Tech Planning, and Engineering Documentation. -- Scaled up engineering teams and established good cross-functional working relationships that increased the overall productivity of the company. Handled build vs buy decisions for various products. -- Led initiatives responsible for 200% growth in student enrollments and a 50% drop in student withdrawals. -- Launched the Growth Experimentation program responsible for 15% increase in enrollment conversions.
I led the Data & Machine Learning Platform team at Amazon Music. My team built tools and platforms to help Scientists and Engineers access, process, compute, experiment, store & share data and build scheduled machine learning and other complex data workflows in production environments. Our platforms ran at Amazon scale processing billions of events per day. My team was closely aligned with Machine Learning, BI, and Product teams and we contributed to multiple cross-team programs. We owned the end-to-end batch data infrastructure at Amazon Music which includes the behavioral data ingestion ETLs, Redshift based data warehouse, Tableau based reporting, and Spark based data processing workflows. We also built platforms for large scale machine learning experimentation, workflow orchestration, and data accessibility. Being the custodians of Amazon Music customers' data, we were responsible for building security and privacy features in our platforms. Our products had high adoption rate and powered crucial features on the Amazon Music app, including personalization and music discovery.
I started the Data Science Platform at Amazon Music. Strategized the ML Platforms at Amazon Music, aligning closely with the central Amazon and AWS ML Platform teams. Worked with AWS Glue and AWS SageMaker teams during the early days of these products and built similar platforms at Amazon Music.