United States
Data and AI engineering leader with 20+ years building the data foundations, evaluation infrastructure, and ML platforms that power production AI at consumer scale. Currently leading Data, Applied Science, and AI at a rapidly growing startup, where I build multi-modal data foundations and evaluation pipelines that power fine-tuning, agentic workflows, and AI agents in a regulated, sensitive domain. The work spans the full GenAI lifecycle — data foundations, eval infrastructure, fine-tuning and distillation, RAG, agent orchestration, and Responsible AI practices. What I've built over 25 years in the industry: — (fast growing,industry leading stratup): end-to-end AI Platform (feature engineering, fine-tuning, RAG, eval, model serving, observability); multi-modal data foundations across structured clinical, behavioral, and unstructured note/voice modalities; agentic harnesses and reusable skills that standardize how the company ships AI products. — At Meta: data strategy for the organizations managing $XXB+ in annual AI infrastructure capacity planning and spend, including AI training and inference optimization. Built forecasting capabilities across 1-, 2-, and 5-year horizons used by leadership across organizations to plan and prioritize capacity spend. — Led teams and orgs that built data infra powering meta's massive scale reliability engineering ensuring automated incident detection and resolution , AI eval infra (hawkeye etc) and production engineering across AI and non-AI fleet. — At Yahoo: the Media Analytics Warehouse (300+ PB, 1M+ daily queries), a lambda-architecture data flywheel serving 1B+ users with <5s streaming latency, a unified user signal store with vectorized embeddings, and Yahoo's first fully automated experimentation platform (5K+ A/B buckets daily). Led orgs of 100+ engineers; secured C-suite sponsorship for multi-year, billion-dollar digital transformation. The thread connecting all of it: turning fragmented data and ML systems into cohesive, production-grade platforms that accelerate research-to- product velocity. Areas I work in: foundation model data & evaluation • data flywheels & annotation pipelines • teacher/student distillation • multi-modal data foundations • LLM and agentic system evaluation • RAG and retrieval • AI platform architecture • modern data stack (Snowflake, BigQuery, lakehouse) • Python, SQL • data governance, privacy, Responsible AI Open to conversations with AI labs, frontier AI companies, and AI-native product organizations building production systems on top of trusted data.
Working with c-suite , Actively hiring and building out teams at a fast growing startup , helping define AI strategy and build data foundations for AI fly-wheel (process , label, train, evaluate , feedback, refine ) Responsibilities span across Data infrastructure and data engineering , Applied Science, and AI infrastructure and foundations . Building multi-modal data foundations, AI Platform to support self care via LLM coach tuned on proprietary data (includes infra for fine-tuning, RAG, eval, model serving), agentic workflows, and AI agents across the company. What I'm building/leading/advising on: - Multi-modal data foundations across structured clinical, behavioral, conversational, and unstructured note/voice modalities — powering fine-tuning, retrieval, and evaluation pipelines for domain-specialized foundation models. - End-to-end AI Platform covering feature engineering, fine-tuning, RAG, prompt and eval management, model serving, observability, and cost controls. - Agentic workflows and AI agents across multiple domains and tools — reusable harnesses, skills, and orchestration patterns that standardize how a small and nimble startup ships AI products. - Evaluation infrastructure for LLM and agentic systems — eval-driven iteration, regression tracking, bias and safety reviews, human-in-the- loop oversight. - Data governance and Responsible AI: PHI handling, HIPAA compliance, ethical AI practices in a regulated, sensitive-care domain. - Cross-functional partnership with Product, Clinical, and Operations leadership; recruiting, mentoring, and leading a team of data engineers, data scientists, applied scientists, ML/AI engineers, and AI platform engineers.
• As an org leader (manager of managers/sr mgrs) my primary responsibility involves building and supporting a high performing engineering culture by hiring and motivating the best talent that could be found in the tech industry . I take a lot of pride in the impact my teams create across the company and across its billions of users • Support multiple charters for Meta's massive scale infrastructure and data needs, developing products to manage end to end observability , auto-remidiation, supply chain and infra capacity tracking for meta scale infra needs . • Collaborate with cross-functional teams to ensure seamless infrastructure support for all platforms. • built innovative solutions to optimize infrastructure efficiency through actionable metric view built on extremely detailed signals logged through millions of servers and services across the company
Led multiple organizations of ~100 engineers and engineering leaders in the space of publisher monetization and analytics , building large scale streaming and batch data processing and targeting systems to optimize yield and improve key advertiser and adtech metrics (CPM,STR etc). Led engineering teams towards enabling integration with large header based bidding platforms. Built and led an org of ~100 high performing engineers and engineering leaders (Managers , Sr Eng managers and directors of engineering ) across data , growth and Monetization function for the company . Team composed of data and software engineers/analysts/scientists, Cloud Computing, Big Data, Growth Engineering, Digital Advertising across mobile, web, app, cross platforms and product development. Analytics & Data Engineering: Built Yahoo's Consumer analytics and data engineering organization ground up - from 0 to a group of ~50 data engineers , data scientists and data governance engineers. Set the vision, drove execution and built the architecture for a distributed data system that process 10s of terabytes of data every day through high performing and robust data pipelines that processed data in realtime and in batch. The system efficiently processed large scale streaming data ( > 1 MM events at peak) and enabled real time querying on data in excess of half an exabyte (500+ PB). The system supported > 3 MM user initiated queries per month across 1000s of internal and external data and product stakeholders.
Took on expanded charter of yahoo's marketing technology and engineering efforts , leading and supporting organization of 100+ engineers and engineering leaders . Organization design and performance management strategy were my key responsibilities during this phase of my transition. Effectively managed a matrixed organizational structure , collaborating very closely with senior most engineering leaders of the company , working with cross functional partners to drive strategic direction of yahoo's engineering efforts on data engineering , analytics ,data science, ads experiences, monetization , marketing technology and digital transformation/ cloud migration and partnership efforts.
Took on additonal responsibility of team and people management during a year of hyper growth and significant org and strategic changes in the company. Went on to build organization of 50+ engineers and engineering leaders that consisted of data engineers , data scientists , software engineers and UI developers across data analytics and ads experiences , monetization for Yahoo's massive media landscape. The platform and experiences built by the organization drove revenue and user growth in 100s of millions of USD across the years. Initiated company wide digital transformation proposal in consultation with the senior most technical leaders , including the CTO , CIO and CFO - resulting in kicking off of partnership with Google Cloud Platform and setting the company on track for modernization of its infrastructure as the strategy shifted more towards artificial intelligence and machine learning. Introduced Tensorflow, cloud vision and autoML based platform modernization for ad creatives and image analysis.
software engineer for CSC's company wide redesign of its HR system , including its interfaces to enterprise systems and platforms as well as analytics products
Engineer and consultant for Oracle's Daily business intelligence suite of products as part of the newly kicked off Oracle fusion platform initiative