Senior AI Architect - Build Production ML for Energy Infra

Solaris Energy Infrastructure

Houston (TX)

Hybrid

USD 170,000 - 250,000

Full time

14 days+
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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.

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