Vetted Google Gemini Professionals

“Lifecycle/CRM marketer with experience at Fandango and Young & Reckless, owning high-volume multi-brand campaign calendars and building Braze-based email/SMS/push journeys. Stands out for tying lifecycle strategy to measurable business impact, including 14% lift in email-attributed revenue, 18% CLTV improvement, and 22% higher activation through behavior-based experimentation.”

“Founding engineer at an edtech startup who combines hands-on engineering leadership with advanced AI-native development workflows. They’ve built an AI grading pipeline and a multi-agent SDLC tool, and stand out for treating AI agents like an engineering team with planning, parallel execution, QA, and rigorous validation.”

“Full-stack engineer who built BrewAI, a cloud-native AI resume optimization platform on GCP using React, TypeScript, LangChain, and Gemini, with scalable async job processing and LLM safety guardrails. The product gained real-world traction when an undergraduate college in India asked students to use it for internship resume drafting, and the candidate also has team lead experience shipping an early-stage ERP system.”

Sreenaina Koujala

Screened

Mid-level Full-Stack & AI Engineer specializing in cloud and intelligent systems

Ashburn, VA8y exp

“Builder with experience across government contracting, engineering automation, and solo AI product development. They architected a serverless AWS pipeline that converted unstructured BIM data into IFC 3D models, built an enterprise internal-data chatbot with auditability and guardrails at Steampunk, and independently launched an AI study platform using Claude. Strong fit for early-stage or ambiguous environments where end-to-end ownership and practical AI systems matter.”

“Built an end-to-end GenAI underwriting copilot at TD Bank for complex financial documents, combining RoBERTa-based risk classification with Azure OpenAI RAG to deliver grounded, citation-based insights. Drove a 40-50% reduction in manual underwriting review time and created reusable FastAPI ML services that cut integration effort for other teams by 30-40%.”