Teams at Vertex, Inc.

Serve as final escalation for complex, visible client technical issues; provide advanced troubleshooting for data-driven applications, databases, APIs, Java, Linux, and networking. Liaise with customers and internal teams during implementations, mentor junior staff, maintain shared environments, create knowledge-base documentation, and participate in on-call rotation.

Lead enterprise model-training strategy for Commercial AI products: fine-tune LLMs (QLoRA/LoRA/PEFT), train traditional ML models, design large-scale data pipelines, enforce data governance and PII handling, build reproducible experiment/training pipelines, optimize GPU/distributed training costs, and mentor teams to operationalize models into production.

Lead design and implementation of the enterprise AI orchestration and retrieval platform: build MCP servers, define tool-surface and multi-agent patterns, design RAG systems and chunking, implement routing/context/window management and observability, set evaluation and safety standards, onboard product teams, and mentor engineers to raise orchestration and retrieval maturity.