Lead AI-Driven Supply Chain Architect (Equity)

Shamrock AI; San Francisco (CA); Híbrido; USD 180.000 - 220.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Early Stage Equity

Full medical, dental, vision

Location: San Francisco

Descripción de la vacante

Shamrock AI is building an agentic data governance platform for large enterprises, helping AI agents safely operate across critical business processes. This role focuses on designing AI agents that understand BOM hierarchies, supplier data feeds, and demand signals to assess data quality, risk, and remediation needs rather than simply returning dashboards.

You will own the data governance framework, define scoring rubrics, prototype end-to-end solutions with LLMs, and lead enterprise deployment

Formación

• Deep experience in global supply chain—manufacturing, semiconductor, or high-tech OEM.
• Built and shipped AI agents using Claude or other LLMs; can write Python end-to-end.
• Data governance mindset with validation rules, failure modes, and risk scoring.
• Enterprise-scale program deployment including COE creation and stakeholder management.

Responsabilidades

• Design and spec AI agents for data intelligence, including validation rule generation and data quality scoring.
• Translate data specifications into structured LLM contexts with grounding.
• Own the enterprise deployment playbook and COE rollout across geographies.
• Lead customer discovery workshops onsite to map data landscapes and risks.
• Draft the v1 product spec and go-to-market roadmap for early expansion.

Conocimientos

Supply Chain Fluency

AI/LLM Practitioner

Data Governance

Enterprise Deployment

Python

Claude

OpenAI GPT

Herramientas

Claude

Python

OpenAI GPT

Descripción del empleo

Shamrock AI is building an agentic data governance platform for large enterprises, helping AI agents safely operate across critical business processes. This role focuses on designing AI agents that understand BOM hierarchies, supplier data feeds, and demand signals to assess data quality, risk, and remediation needs rather than simply returning dashboards.

You will own the data governance framework, define scoring rubrics, prototype end-to-end solutions with LLMs, and lead enterprise deployment