Director, AI Engineering — Enterprise AI Platform Leader

Venture Global LNG; Arlington (VA); On-site; USD 221,000 - 260,000; Full time

Job summary

Venture Global LNG in Arlington, VA seeks a Director of AI Engineering to define and execute the enterprise AI strategy, architecture, and operating model. You will build a cross-functional team of senior AI and ML engineers, drive platform capabilities, and ensure security-first AI deployments that align with business priorities.

This hands-on leadership role requires deep technical judgment, stakeholder communication, and a track record of delivering production AI/ML systems at scale.

Qualifications

• 10+ years of experience in software, data, or machine learning engineering, including 3+ years leading technical teams.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field of study.
• Demonstrated experience architecting and deploying production AI/ML systems at enterprise scale.
• Hands-on experience with large language models, including self-hosting open-weight models and serving optimization (e.g., quantization, inference optimization, GPU utilization).
• Experience designing and deploying agentic AI systems and the frameworks/patterns that support them.
• Strong proficiency in Spark, Python and modern AI/ML tooling.
• Experience building on cloud platforms and on-premises GPU infrastructure.
• Proven ability to hire, lead, and mentor high-performing engineering teams.
• Experience with infrastructure procurement, capacity planning, and vendor management.
• Excellent interpersonal and communication skills, with the ability to translate technical concepts for executive and business audiences.
• Strong work ethic with the ability to effectively prioritize, meet deadlines, adapt to changing priorities, and succeed in a fast-paced environment.

Responsibilities

• Define and execute the AI engineering strategy, roadmap, and operating model for the enterprise, aligned to business and operational priorities.
• Build, lead, and mentor a team of senior AI engineers, platform engineers, applied AI engineers, and machine learning engineers.
• Architect scalable, secure infrastructure for AI agent development and deployment across cloud and on-premises environments.
• Lead the strategy for self-hosted open-weight large language models (LLMs), including model selection, fine-tuning, quantization, and serving optimization, while integrating commercial API-based models where appropriate.
• Establish the reference architecture and engineering standards for agentic systems that analyze both batch and streaming data for operational and commercial use cases.
• Partner with Data Engineering on ontology and semantic model design to ground AI systems in trusted enterprise data.
• Oversee procurement of GPU servers and AI infrastructure, managing vendor relationships, capacity planning, and budget.
• Partner with business unit leaders to identify and prioritize high-value AI use cases and drive them from concept to production.
• Explore and enable development of custom machine learning models alongside LLM-based approaches.
• Establish MLOps/LLMOps practices, model governance, monitoring, and documentation standards for maintainability and reliability.
• Collaborate with IT and security leadership to operate within energy-sector security and governance frameworks.
• Report on team performance, project outcomes, and business impact to executive leadership.

Skills

Python

Spark

AI/ML tooling

Large language models

Leadership

Cloud platforms

GPU infrastructure

Education

Bachelor's degree

Tools

Databricks

Job description

Venture Global LNG in Arlington, VA seeks a Director of AI Engineering to define and execute the enterprise AI strategy, architecture, and operating model. You will build a cross-functional team of senior AI and ML engineers, drive platform capabilities, and ensure security-first AI deployments that align with business priorities.

This hands-on leadership role requires deep technical judgment, stakeholder communication, and a track record of delivering production AI/ML systems at scale.