Vetted Recommender Systems Professionals

Sandeep Rohilla

Screened

Principal Platform Engineer specializing in AI-driven document automation

San Francisco, CA20y exp

“Backend engineer who built an event-driven, multi-service resume review system integrating AI/ML workflows. Demonstrated strong performance engineering (e.g., composite indexing dropping latency from ~600ms to ~35ms and major P95 gains) and high-throughput pipeline optimization via caching, batching, and worker concurrency tuning, with multi-tenant isolation implemented across DB and Redis.”

Edward Yeh

Screened

Director-level Data Engineering & MDM leader specializing in enterprise data platforms

Hunt Valley, MD20y exp

“Former Xendit (YC-backed fintech) operator applying outcome-driven, scalable product-building experience to a new startup: a real-time, personalized real estate investment intelligence platform. Has begun prototyping, completed ROI analysis, and validated the space with US market research plus broker interviews in Chicago and Los Angeles, aiming to differentiate from Zillow/Redfin with goal-based ranked investment recommendations.”

“Engineering leader with experience at CBS Interactive and Paramount who scaled a web engineering team from 4 to 30+ (adding QA/PMO/mobile) while instituting strong agile and code-quality processes. Led a major architectural shift to a generic content API that decoupled web/mobile experiences from niche publishing systems, reportedly cutting developer onboarding time by ~50% and enabling some day-one production commits.”

“Built both traditional data infrastructure and LLM-powered product workflows, spanning a Python/SQL ETL deployment at Amazon and an adaptive learning system for their DataLingo platform. Particularly interesting for roles at the intersection of data engineering, applied AI, and customer-facing product delivery, with hands-on experience stabilizing probabilistic LLM systems in production.”

“Product leader and former co-founder/CPO who built a K-12 tutoring marketplace end-to-end and later led AI personalization work at Mattel. Particularly compelling for mission-driven edtech roles: they combine deep two-sided marketplace and trust/safety experience with a clear philosophy that AI should strengthen, not replace, human tutoring relationships.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”