Vetted Workflow Automation Professionals

“Non-traditional hockey background but demonstrates strong transferable skills for athlete guidance: research-driven evaluation, structured planning, and ongoing support. Has proven mentoring results (tutoring improved a student’s Algebra grade from 85 to 93) and relationship-building that contributed to acceptance into a graduate program and completion of a master’s degree.”

“Built and shipped a production LLM-powered document processing agent (ingestion→OCR→LLM extraction/classification→validation→DB/workflow triggers) using Kafka and PostgreSQL. Emphasizes production reliability with strict JSON schemas, idempotent services, retries/backoff, fallback models, and human-in-the-loop review—driving ~90% automation, minutes-to-seconds processing, and ~10x throughput.”

Rasheed Samady

Screened

Entry-level AI Engineer specializing in automation and ML platforms

San Francisco, CA0y exp

“Built a production Python lead intelligence pipeline that combined external APIs, website crawling, and automated opportunity brief generation, with strong emphasis on reliability, observability, and recovery. Also has hands-on Playwright experience hardening flaky, dynamic web automations and reducing intermittent failures to under 5% through logging, screenshots, session management, and retry strategies.”

“Backend ERP developer specializing in Odoo (Python MVC) with hands-on experience integrating ERP workflows with external SQL databases and handling cloud deployment compatibility issues. Led a migration of ~40 years of legacy data into a modern ERP using scripted transforms and unique identifiers to preserve data integrity, and has experience implementing role-based permissions and preventing failure modes in SQL status update flows.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”