AI Architect

Solaris Energy Infrastructure•Houston, TX

22h•Hybrid

About The Position

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.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or a related technical field; Master's degree preferred
5+ years in software or AI/ML engineering, with at least 2 years in a senior or lead technical capacity
Hands-on experience designing and deploying LLM-powered applications in production, including RAG pipelines, agentic workflows, tool use, and function calling
Working knowledge of MCP (Model Context Protocol) or equivalent AI context and integration frameworks
Demonstrated experience with agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, or equivalent
Strong Python proficiency and REST API development experience
Experience with cloud deployment and infrastructure on Azure, AWS, or GCP
Proven ability to take AI tools from prototype to production — not just building, but maintaining and scaling
Ability to explain architectural decisions to non-technical stakeholders and run practical enablement sessions with business teams

Nice To Haves

Experience in energy, oilfield services, industrial equipment, or field-operations-heavy industries
Familiarity with equipment management systems, ERP platforms, or field service management software
Track record of building AI governance frameworks, security patterns, or responsible AI policies
Experience at a mid-market company where you owned technical decisions end to end
Prior experience standing up an AI function or AI platform from scratch

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