Supply Chain Planning and Operations (SCPO) AI Lead
Intel
Opportunity published from Workday · applications stay with the original hiring source.
About the opportunity
The Supply Chain Planning Operations (SCPO) organization is seeking an AI Software Architect to serve as the SCPO AI Lead.
This is a founding technical leadership role embedded within supply planning operations to define and execute the AI strategy for connecting planning and execution data, detecting emerging supply and demand risks, and enabling planners and leaders to act on trusted, explainable insights.
The role will architect and build the intelligent stitching and alerting layer across Plan of Record (POR), Long Range Planning (LRP), Sales and Operations Planning (SnOP), Enterprise Resource Planning (ERP), and other supply chain data sources.
You will convert fragmented data and manual reconciliation into production capabilities that continuously monitor supply execution, identify likely failures, explain drivers, and guide timely intervention.
Key responsibilities
- Define the SCPO AI and data intelligence strategy, architecture, roadmap, and standards in alignment with supply-chain priorities.
- Architect and operationalize a trusted data stitching layer across POR, LRP, SnOP, ERP, and other planning data sources, including lineage, controls, and data-quality monitoring.
- Develop production machine-learning and AI capabilities for time-series analysis, anomaly detection, root-cause identification, and supply-risk sensing.
- Integrate AI outputs with enterprise planning systems and operational workflows using reliable APIs, data pipelines, monitoring, and override mechanisms.
- Build agentic workflows that automate recurring analyses and exception triage while maintaining human-in-the-loop controls and auditability.
- Develop scenario and sensitivity capabilities that evaluate supply disruptions, demand changes, and capacity reallocations across planning horizons.
- Create explainable alerts and decision-support experiences that show what changed, why it matters, confidence levels, and recommended actions.
- Partner with supply planning, manufacturing, finance, data engineering, and IT to translate operational problems into scalable technical solutions.
- Establish MLOps and software-engineering practices for model versioning, testing, deployment, observability, security, and responsible AI governance.
Qualifications
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Industrial Engineering, Operations Research, Applied Mathematics, or a related quantitative field.
- 8+ years of experience in machine-learning engineering, AI engineering, data science, data engineering, optimization, or related technical roles.
- Expertise in architecting, deploying, and operating machine-learning solutions in production on complex enterprise data.
- Programming experience in Python and strong SQL skills, with practical experience in modern machine-learning and software-engineering frameworks.
- Experience designing data pipelines, APIs, and integrations across enterprise applications and operational systems.
- Experience leading cross-functional technical work and influencing architecture and delivery decisions.
- This position is not eligible for Intel immigration sponsorship.
Nice to have
- Master's degree in a relevant technical or quantitative discipline.
- Experience in semiconductors, electronics, or comparable high-volume manufacturing environments.
- Working knowledge of supply planning, demand planning, SnOP, capacity planning, and inventory optimization.
- Experience with enterprise planning and manufacturing platforms such as SAP, Kinaxis Rapid Response, or Oracle.
- Hands-on experience with cloud data and AI platforms, distributed data processing, and enterprise-grade observability.
Benefits
- Competitive pay and stock bonuses.
- Comprehensive health benefit programs.
- Retirement programs.
- Vacation and paid time off.
Annual Salary Range
- $170,500.00-315,490.00 USD
Job Type
Experienced Hire
- Location: US, California, Folsom (Additional locations: US, Arizona, Phoenix; US, California, Santa Clara; US, Oregon, Hillsboro)
Remote/Hybrid Status
Hybrid work model (split time between on-site and off-site)
Work Authorization
Not eligible for Intel immigration sponsorship
Application: UpVagas lists this opportunity from the hiring company or its recruitment platform. The application is completed at the original source.
Key details from the source
- Experience with large language models, retrieval-augmented generation, agentic frameworks, and generative AI governance.
- Experience building interactive scenario-modeling or decision-support applications.
- Experience hiring, mentoring, and technically leading AI, machine-learning, or data-engineering talent.
Full listing
UpVagas condensed repetitive or legal boilerplate to make this page easier to read. The original hiring source contains the complete job description.
