AI Architect

SoftPathTechnologies; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Referral bonus

Job summary

SoftPathTechnologies is seeking an AI Architect to drive onsite AI strategy and governance for QA transformation in Houston. The role entails shaping an enterprise AI architecture, defining standards for LLMs, generative AI, AI agents, data, APIs, and model validation, and leading cross-team collaboration to deliver scalable AI solutions.

The position is an onsite, 12-month contract in Houston, with leadership responsibility for governance checkpoints, KPIs, and vendor alignment, while

Responsibilities

• Establish and evolve the AI vision, roadmap, operating model, and governance framework for the QA organization.
• Develop an accountability model across AI planning, governance, architecture, vendor management, innovation, and value realization.
• Create centralized processes for AI use-case intake, prioritization, risk assessment, and approval.
• Establish 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 standards and recommended patterns for: Large Language Models (LLMs), Generative AI, AI agents and orchestration, Knowledge sources and retrieval, Data architecture, APIs and integrations, Prompt engineering, Model evaluation and validation.
• Develop reusable reference architectures and technical patterns that can be leveraged across multiple teams and vendors.
• Establish architectural review processes for new AI initiatives and solutions.
• Ensure AI solutions are scalable, interoperable, secure, supportable, and aligned with enterprise architecture standards.
• Identify opportunities to apply AI across: Test design and test case generation, Test automation, Quality intelligence, Defect analysis, Release readiness, Automation monitoring, Reporting automation, Knowledge agents, Engineering productivity.
• Provide technical oversight for high-impact AI initiatives within QA.
• Partner with QA engineers, automation engineers, developers, and delivery teams to transition AI concepts and proofs of concept into production-ready capabilities.
• Define architecture and integration approaches across enterprise platforms including:

Job description

AI Architect
Location: Onsite Houston, TX 3x/ week
Duration: 12 Months Contract
on W2
Referral: $5/hr
Visa: USC, GC, GC-EAD, TN

Job Description

Position Overview

Key Responsibilities

AI Strategy & Governance

• Establish and evolve the AI vision, roadmap, operating model, and governance framework for the QA organization.
• Develop an accountability model across AI planning, governance, architecture, vendor management, innovation, and value realization.
• Create centralized processes for AI use-case intake, prioritization, risk assessment, and approval.
• Establish 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.

Enterprise AI Architecture

• Design enterprise AI architecture supporting software testing and QA transformation.
• Define standards and recommended patterns for:
  • Large Language Models (LLMs)
  • Generative AI
  • AI agents and orchestration
  • Knowledge sources and retrieval
  • Data architecture
  • APIs and integrations
  • Prompt engineering
  • Model evaluation and validation
• Develop reusable reference architectures and technical patterns that can be leveraged across multiple teams and vendors.
• Establish architectural review processes for new AI initiatives and solutions.
• Ensure AI solutions are scalable, interoperable, secure, supportable, and aligned with enterprise architecture standards.

QA & Software Testing Transformation

• Identify opportunities to apply AI across:
  • Test design and test case generation
  • Test automation
  • Quality intelligence
  • Defect analysis
  • Release readiness
  • Automation monitoring
  • Reporting automation
  • Knowledge agents
  • Engineering productivity
• Provide technical oversight for high-impact AI initiatives within QA.
• Partner with QA engineers, automation engineers, developers, and delivery teams to transition AI concepts and proofs of concept into production-ready capabilities.

Technology & Integration Architecture

Define architecture and integration approaches across enterprise platforms including: