Vetted Requirements Gathering Professionals

“HRBP/Employee Relations professional with Accenture and Clyde & Co experience, combining strong people analytics with risk-focused change management. Notably coded and analyzed four years of exit interview data to drive targeted retention and compensation actions across offices, and partnered with North America HR/Finance leadership on shared-services transition planning involving protected-class risk analysis.”

Peeyush Dyavarashetty

Screened ReferencesModerate rec.

Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems

Miami, FL2y exp

“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”

“IoT/connected-device and SaaS product builder with deep connected health/telehealth experience, including patient care delivery and remote patient monitoring. In their current org, they expanded a nutrition product business by prototyping and piloting a digital pre/post-surgical coaching care-delivery service with real providers/clinics/patients, then building an MVP and taking it to market.”

“Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.”

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“Former Deloitte consultant turned product and strategy leader with 10+ years in high-growth tech, spanning Jet.com, Walmart eCommerce, The Inside, and Togetherwork. Brings a rare mix of hands-on product ownership, supply chain and eCommerce expertise, and executive-level strategic leadership including board-facing analyses, OKRs, and company-wide operational initiatives.”

“Product leader at Nike who launched an AI-powered conversational assistant for wholesale partners on Nike.net, using LLMs, RAG, guardrails, and human escalation to balance innovation with trust. Demonstrates strong human-centered AI judgment, measurable product impact, and a practical philosophy of using AI to augment rather than replace people.”

“UX/product designer with deep healthcare and mission-critical software experience across 3M Healthcare, GE Healthcare, and Motorola. Has designed complex lab automation and radiology workflows end-to-end, combining rigorous field research with hands-on engineering (HTML/CSS/TypeScript/React, Storybook) and even building live prototypes (Firebase + Angular) and production-ready UI control libraries to ship.”

“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”