Director of Enterprise AI

About Us

QISG leverages Quanta’s comprehensive resources to deliver collaborative solutions for our partners' energy infrastructure needs. We use in-house talent, expertise and resources to plan, design, engineer, manage, conduct maintenance on and construct projects.

Our turnkey service capabilities provide our customers with efficiency, consistency, attention to detail and safe execution. The QISG team brings together Engineering, Safety, Quality, Material Procurement, QA/QC, Right-of-Way Acquisition, Scheduling, Environmental Planning, Permitting, Title and Land Management expertise that ensure outstanding results for our clients.

Domestic travel up to 25% may be required for periodic visits to field and regional offices.

QISG is an engineering, procurement, and construction (EPC) leader transforming the renewable energy infrastructure landscape.

We are seeking a Director of Enterprise AI to build QISG’s AI capabilities from the ground up
. In this role, you will define our AI strategy, design and deploy production‑ready solutions, and create a high‑performing AI team that drives measurable impact across engineering, construction, safety, and field operations.

This is a rare opportunity to combine strategic vision, hands-on technical expertise, and leadership to shape the future of AI at QISG
, establishing how advanced analytics and intelligent systems improve project delivery, efficiency, and operational outcomes.

The ideal candidate will have proven experience building enterprise-level AI strategy and teams, delivering successful AI projects from concept to production
, and driving adoption across complex organizations.

You will lead the creation of the AI roadmap, grow the team, and drive adoption across the organization—transforming how we plan, design, and execute major utility infrastructure projects.

• 7+ years of experience in data science and machine learning
  - including 3 years leading AI projects or teams.

• Demonstrated success deploying enterprise-level AI solutions into production—including LLMs, NLP, computer vision, and predictive analytics.

• Proven ability to translate complex AI capabilities into clear business value for executives and operational teams.

• Strong proficiency in Python
  , modern AI/ML frameworks, cloud-based AI services, and digital transformation initiatives.

• Experience using AI to automate manual or data-heavy workflows such as materials management
  , cost controls
  , scheduling
  , and QA/QC
  .

• Preferred: Background in EPC or heavy construction, including integration with ERP systems and BIM/CAD environments.

Strategic Leadership

· Define and execute the company’s AI strategy and roadmap, aligned to business goals and operational realities.

· Identify and prioritize high-impact AI use cases across departments (design, estimating, field operations, safety, supply chain, etc.).

· Translate complex technical opportunities into clear business value and communicate effectively with executive leadership.

Technical Execution

· Architect and deploy AI/ML solutions leveraging cloud-native platforms (Azure, AWS) and enterprise data sources.

· Build and maintain AI pipelines, including data ingestion, RAG (Retrieval-Augmented Generation), Agentic build, and model orchestration.

· Establish and enforce enterprise-wide data governance standards (e.g., data quality, ownership, PII) specifically for large-scale engineering and project management data.

· Deliver working prototypes and MVPs quickly — moving from proof of concept to production.

Team and Vendor Leadership

· Build and lead a small AI team (e.g., data engineer, ML engineer, AI developer) within 6–12 months.

· Evaluate and manage external vendors or consulting partners for specialized AI services or accelerators.

· Mentor team members and promote a culture of innovation, experimentation, and responsible AI.

Operational Integration

· Work with operations, project management, and engineering leaders to embed AI solutions into workflows.

· Establish metrics and feedback loops to measure performance and ROI of deployed AI tools.

· Drive change management and adoption across the business.

·…