AI Architect

Posted 17 Days Ago
Be an Early Applicant
Houston, TX, USA
In-Office
Senior level
Logistics • Energy • Industrial • Manufacturing
The Role
Build and own Solaris’s AI foundation, including LLM applications, RAG pipelines, agentic workflows, MCP servers, data pipelines, MLOps, integrations, and governance. Partner with business teams to identify use cases, deliver production-ready tools, provide AI enablement, establish responsible-use standards, and measure adoption, productivity, and ROI across energy and field-service operations.
Summary Generated by Built In
Company Description

About Solaris Energy Infrastructure

Solaris Energy Infrastructure, Inc. (NYSE:SEI) provides scalable equipment-based solutions for use in distributed power generation as well as the management of raw materials used in the completion of oil and natural gas wells. Headquartered in Houston, Texas, Solaris serves multiple U.S. end markets, including energy, data centers, and other commercial and industrial sectors.

Job Description

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.

 

Essential Functions

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

Qualifications

Experience/Education

Required

  • 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

Strongly Preferred

  • 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

 

Key Skills and Qualifications

  • Exceptional communicator – direct and transparent, skilled problem-solver with proven success in building coalitions and avoiding conflicts
  • Total ownership mentality – proactively identifies and removes obstacles across numerous ongoing tasks
  • Independent thinker – provides original thoughts and constantly asking "how can we do this better"
  • Innovative thinker – willingness to consider novel solutions and ability to adapt to change
  • Desirable teammate – impeccable character, humility, and collaborative
  • Relentless – aspires to contribute and achieve his/her full potential

Additional Information

Our CREATORS Culture
At Solaris, we believe that staying true to our core beliefs improves our decision-making, productivity and is key to our individual and collective achievements. Combining your innovative thinking with our core values that encourage Communication, Recognition, Entrepreneurship, Accountability, Teamwork & Transparency, Ownership, Results and Safety, we become CREATORS.

We value your hard work, integrity, and commitment to the Solaris “First in Service & Innovation” culture through competitive pay and benefits packages and ongoing career development.

  • Competitive compensation packages
  • Medical, Dental & Vision benefits
  • Disability Insurance
  • Company paid Life and AD&D insurance with supplemental offerings
  • Company matching 401(k) retirement plan
  • Paid time off, including 10 paid holidays
  • Career Progression
  • Tuition Reimbursement

This job overview is not all inclusive. In addition, Solaris reserves the right to amend this job overview at any time. Solaris is an Equal Opportunity Employer.

Why Solaris Join a company at the forefront of the energy infrastructure buildout powering data centers and industrial growth. We offer competitive compensation, benefits, and opportunities to grow alongside a high-performing team.

Skills Required

  • Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
  • 5+ years of experience in software or AI/ML engineering
  • At least 2 years in a senior or lead technical capacity
  • Hands-on experience designing and deploying production LLM-powered applications, including RAG pipelines, agentic workflows, tool use, and function calling
  • Working knowledge of MCP or equivalent AI context and integration frameworks
  • Experience with agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, or equivalent
  • Strong Python proficiency
  • REST API development experience
  • Experience with cloud deployment and infrastructure on Azure, AWS, or GCP
  • Ability to take AI tools from prototype to production, including maintenance and scaling
  • Ability to explain architectural decisions to non-technical stakeholders and conduct practical enablement sessions
  • Master’s degree
  • Experience in energy, oilfield services, industrial equipment, or field-operations-heavy industries
  • Familiarity with equipment management systems, ERP platforms, or field service management software
  • Experience building AI governance frameworks, security patterns, or responsible AI policies
  • Experience at a mid-market company owning technical decisions end to end
  • Prior experience standing up an AI function or AI platform from scratch
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The Company
471 Employees
Year Founded: 2014

What We Do

Solaris Energy Infrastructure provides proprietary power generation, control, and distribution solutions along with logistics equipment and services. Founded in 2014, the company serves data center, energy, commercial, and industrial customers. Its offerings include rapidly deployable, integrated power infrastructure and specialized automated systems and field services that support efficient, safe oil-and-gas wellsite operations and other critical power workloads across demanding markets.

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