AI Architect

Ora Apps Inc.; United States; Hybrid; USD 180,000 - 230,000; Part time

Job summary

Ora Apps Inc. is seeking an AI Architect for a 12-month contract in Houston, TX, with a hybrid work arrangement. You will establish the AI vision, roadmap, governance framework, and architecture to lead QA transformation and scalable AI solutions.

Work closely with Enterprise Architecture, Security, Data, and Responsible AI teams to define KPIs, governance checkpoints, and reusable patterns for LLMs, Generative AI, and AI Agents, ensuring secure, interoperable implementations.

Responsibilities

• Establish and evolve AI vision, roadmap, operating model, and governance for QA.
• Develop accountability models covering AI planning, governance, architecture, vendor management, innovation, and value realization.
• Establish centralized processes for AI use-case intake, prioritization, risk assessment, and approval.
• Define governance checkpoints, stage gates, KPIs, and executive reporting for AI initiatives.
• Partner with Enterprise Architecture, Security, Data, and Responsible AI teams to align with standards.
• Design enterprise AI architecture to support software testing and QA transformation.
• Define architecture standards and reusable patterns for LLMs, Generative AI, AI Agents, orchestration, RAG/knowledge retrieval, data architecture, APIs, integrations, prompt engineering, and model evaluation/validation.
• Establish architectural review processes to ensure scalable, secure, interoperable, and enterprise-aligned AI solutions.

Skills

AI architecture

Governance

Vendor management

Enterprise Architecture

Security

Data

Responsible AI

LLMs

Tools

LLMs

Job description

I’m reaching out regarding an AI Architect opportunity with a 12-month contract that is Houston, Texas - Hybrid .

Position: AI Architect

Duration: 12+ Months

Location: Houston, Texas - Hybrid

Key Responsibilities:

• Establish and evolve the AI vision, roadmap, operating model, and governance framework for the QA organization.
• Develop accountability models covering AI planning, governance, architecture, vendor management, innovation, and value realization.
• Establish centralized processes for AI use-case intake, prioritization, risk assessment, and approval.
• Define governance checkpoints, stage gates, KPIs, and executive reporting for AI initiatives.
• Partner with Enterprise Architecture, Security, Data, and Responsible AI teams to ensure alignment with organizational standards.
• Design enterprise AI architecture supporting software testing and QA transformation.
• Define architecture standards and reusable patterns for LLMs, Generative AI, AI Agents, orchestration, RAG/knowledge retrieval, data architecture, APIs, integrations, prompt engineering, and model evaluation/validation.
• Establish architectural review processes and ensure AI solutions are scalable, secure, interoperable, supportable, and aligned with enterprise standards.