First Director of AI for Engineering & Data-Driven Impact

Allen Austin; Houston (TX); On-site; USD 180,000 - 280,000; Full time

Job summary

Allen Austin, partnering with a leading Houston‑based engineering firm, seeks its first Director of AI to own and scale AI initiatives across engineering disciplines.

This hands‑on role reports to the CEO, defining problems, delivering working tools to engineers, and measuring impact to drive time savings, cost reduction, and quality improvements. The ideal candidate has extensive AI/ML leadership experience and a track record with production LLM applications.

Qualifications

• 8+ years in AI/ML or data science
• 3+ years leading teams or major initiatives
• Production delivery of modern LLM applications (RAG, agents, prompt engineering)
• Experience with regulated or safety-critical industries such as energy, aerospace, medical devices, or defense
• Exposure to reliability engineering concepts and cloud services is a plus

Responsibilities

• Make decades of reports and data searchable with citations and access controls
• Build AI-assisted workflows for proposals, failure analysis, and reporting
• Collaborate on ERP upgrade and Power BI integration to unify hours, revenue, and project data
• Establish AI governance covering confidentiality, ITAR/EAR, IP, and model validation
• Drive adoption through training and change management across business units
• Report value, risk, cost, and ROI to CEO and Board
• Scope AI-enabled client offerings leveraging AWS partnerships and firm data

Skills

AI/ML leadership

LLM applications

Data engineering

Governance & security

Education

Bachelor’s degree in engineering/computer science

MS or PhD strongly preferred

Tools

AWS Bedrock

SageMaker

Power BI

Dynamics 365

Job description

Allen Austin, partnering with a leading Houston‑based engineering firm, seeks its first Director of AI to own and scale AI initiatives across engineering disciplines.

This hands‑on role reports to the CEO, defining problems, delivering working tools to engineers, and measuring impact to drive time savings, cost reduction, and quality improvements. The ideal candidate has extensive AI/ML leadership experience and a track record with production LLM applications.