Principal OT AI Solution Architect

Chevron is accepting online applications for the position Principal AI Engineer through November 2nd, 2026 at 11:59 p.m. (Central Time).

We are seeking an OT Solutions Architect specializing in artificial intelligence to define how AI capabilities move safely and consistently from concept and field trial into supported operational use. This role establishes the reference architectures, deployment patterns, model lifecycle controls, safety guardrails and operational readiness criteria required for AI solutions in live industrial environments.

This position is part of the OT Artificial Intelligence Team, responsible for providing technical leadership and execution support for the evaluation, architecture and operationalization of AI in OT environments. The role enables OT AI priorities by turning proven AI capabilities into repeatable, secure and supportable designs that can be adopted across business units without creating isolated solutions.

Our team is highly technical, creative and cross-functional. The architect will shape the standards that govern AI-enabled operator assistance, computer vision, predictive and prescriptive analytics, intelligent automation, agentic workflows and physical AI across operational environments. Success means accelerating business value while maintaining safety, cybersecurity, reliability, human oversight and clear accountability for AI behavior.

This is a dedicated OT AI architecture role. It covers the design, evaluation, deployment and governance of artificial intelligence capabilities used in industrial operations, including AI at the edge, retrieval augmented generation, computer vision, predictive and prescriptive models, generative AI, agentic systems and physical AI. The role works across OT domains only as needed to ensure AI solutions are safe, secure, reliable and supportable.

Responsibilities for this position may include but are not limited to:

• Author and shepherd approved OT AI reference architectures and reusable design patterns through OT Architecture and cybersecurity review.

• Define guardrails for deploying and operating AI models and agents in industrial environments, including human oversight, fail-safe behavior, degraded modes, rollback, explainability and auditability.

• Establish architecture patterns for edge AI, retrieval augmented generation, computer vision, predictive and prescriptive analytics, generative AI, agentic systems and physical AI.

• Own OT AI model lifecycle architecture, including model intake, validation, versioning, deployment, monitoring, drift detection, retraining triggers, retirement and rollback.

• Define requirements for AI training, validation and inference data, including provenance, quality, labeling, contextualization, access controls and permitted movement across security environments.