Vetted Workflow Automation Professionals

“Asset Management Risk professional at Fidelity Investments who built and productionized an agentic RAG platform enabling compliance and analysts to query 10,000+ fund documents with cited answers in seconds. Implemented structure-aware semantic chunking (AWS Textract), hierarchical retrieval, and hybrid search to raise accuracy from 68% to 94%, and built an evaluation framework tracking accuracy/latency/cost/hallucinations—delivering 40+ hours/month saved and zero critical production failures.”

“Tesla sourcing/supplier readiness professional focused on critical lithium-ion battery components, owning end-to-end supplier onboarding and delivery execution. Uses SQL and Power BI to run integrated readiness plans across samples/approvals/tooling and proactively mitigates cost and import-duty risks while improving supplier performance through structured execution cadences.”

“Built and deployed a production generative AI chatbot at NVIDIA using LangChain + GPT-3 integrated with internal data sources, cutting response time nearly in half and improving CSAT by ~12 points. Also delivered LLM-driven QA tools by fine-tuning Hugging Face transformer models and deploying via an AWS-based pipeline (Lambda/Glue/S3) with orchestration (Airflow/Step Functions), CI/CD, Kubernetes, and monitoring (MLflow/Splunk/Power BI).”

“Consulting project manager in global trade/compliance and regulatory reporting, leading cross-functional initiatives for global clients (tax, customs, supply chain, IT, finance) including US tariff exposure mitigation and EU carbon reporting. Built repeatable automations in Alteryx for US Customs Reconciliation filings (replacing large Excel models) and drives executive alignment through concise, decision-ready briefs and strong governance.”

“Full-stack engineer who built and owned a production real-estate search platform (advanced search + saved-search alerts) using Next.js App Router/TypeScript with a NestJS + Postgres + Elasticsearch/Kafka backend. Demonstrated strong performance engineering (map search FPS ~20→60, ~80% latency reduction) and backend scalability (optimized alert-matching queries and orchestrated notification workflows with Airflow/Redis), with measurable post-launch engagement gains (+27% returning users).”