AI Architect

About the Opportunity

Solaris Energy Infrastructure is building its AI capability from the ground up. Across our power generation and oilfield services equipment rental businesses, the opportunity to apply AI to operational workflows, equipment management, dispatch, and field services is significant and largely untapped. This role exists to build the right foundation before scale. The AI Architect is a senior hybrid position combining deep technical ownership of AI systems with hands-on responsibility for driving AI adoption across the organization. You will own both the technical infrastructure that makes AI reliable and production-ready, and the organizational work that turns that infrastructure into tools people actually use. This role is weighted toward technical depth, but the adoption mandate is real and non-negotiable. Candidates who are purely architectural without the ability to drive organizational change will not succeed here. Getting both right from the start is what separates a lasting AI capability from a collection of disconnected pilots. This is a foundational role — the person who fills it will build the AI systems and organizational capability that Solaris runs on for years to come.

Responsibilities

• Build and own the AI technical foundation
• Design and implement the end-to-end AI systems architecture, including LLM integration patterns, RAG pipelines, agentic frameworks, and MCP server infrastructure
• Own model selection and evaluation — assess, benchmark, and recommend LLMs and AI tools aligned to Solaris's use cases and risk tolerance
• Build and maintain data pipelines that feed AI systems with clean, structured, and contextually relevant information
• Establish MLOps practices for deploying, monitoring, versioning, and maintaining AI applications in production
• Design API and integration patterns connecting AI capabilities to existing business systems, including ERP, field service management, equipment tracking, and internal tools
• Define and enforce AI security, data privacy, and governance standards across all AI systems at Solaris
• Develop and manage MCP servers that give AI models structured access to internal data sources and workflows
• Drive AI adoption across the organization
• Partner with the Director of Software Engineering to translate business priorities into AI use cases and a sequenced delivery roadmap
• Work directly with department teams — field operations, dispatch, finance, and equipment management — to identify high-value AI opportunities and build tools they will actually use
• Design and deliver practical AI training and enablement resources that make AI accessible to non-technical teams
• Champion responsible AI use across the organization, building guardrails, governance practices, and acceptable use policies that give Solaris confidence to move fast
• Track and communicate adoption metrics, productivity gains, and ROI across AI initiatives
• Stay current on AI tooling, industry trends, and energy sector AI applications, bringing relevant opportunities to the team proactively

Requirements

• Bachelor's degree in Computer Science