Senior AI Architect - Build Production ML for Energy Infra

Solaris Energy Infrastructure; Houston (TX); Hybrid; USD 170,000 - 250,000; Full time

Benefits offered by this job

Medical, Dental & Vision

Disability Insurance

Life and AD&D insurance

401(k) retirement plan with company匹配

Paid time off and holidays

Tuition Reimbursement

Job summary

Solaris Energy Infrastructure, Inc. is building its AI capability from the ground up in Houston. The AI Architect role combines deep technical ownership of AI systems with hands-on responsibility for adoption across the organization.

You will own both infrastructure and the organizational work to make AI tools usable, with emphasis on secure, scalable production-grade solutions and governance.

Qualifications

• Bachelor's degree in CS/Software Engineering or related field; Master's preferred.
• 5+ years in software or AI/ML eng, with 2+ years in senior/lead role.
• Hands-on experience designing and deploying LLM-powered apps in prod, incl. RAG pipelines and agentic workflows.
• Experience with MCP or equivalent AI context/integration frameworks.
• Proven ability to scale AI tools from prototype to production.

Responsibilities

• Design end-to-end AI systems architecture with LLM integration, RAG, and MCP server infra.
• Own model selection, evaluation, and benchmarking for Solaris use cases.
• Build data pipelines feeding AI systems with clean, contextual data.
• Establish MLOps practices for deployment and monitoring in production.
• Drive AI adoption with cross-functional teams and provide practical enablement.

Skills

Exceptional communicator

Ownership mindset

Independent thinker

Innovative thinker

Results-driven

Education

Bachelor's degree in CS/Software Engineering

Master's degree preferred

Tools

LangChain

LlamaIndex

CrewAI

Python

REST API

MCP (Model Context Protocol)

Job description

Solaris Energy Infrastructure, Inc. is building its AI capability from the ground up in Houston. The AI Architect role combines deep technical ownership of AI systems with hands-on responsibility for adoption across the organization.

You will own both infrastructure and the organizational work to make AI tools usable, with emphasis on secure, scalable production-grade solutions and governance.