Director of Enterprise AI

Director of Enterprise AI

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.

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

• 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

• 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

• 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

• 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

• 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
• Establish AI ethics, compliance, and safety critical deployment standards

• 7+ years of experience in data science, machine learning, RPA, or AI solution architecture
• 3+ years leading AI projects and people in production environments
• Proven experience designing and deploying solutions using LLMs, NLP, computer vision, or predictive analytics
• Ability to communicate technical solutions clearly to non‑technical stakeholders including Executive Level presentations
• Demonstrated success delivering measurable business outcomes from AI initiatives

• Strong hands‑on proficiency with Python and major AI/ML frameworks (PyTorch, Tensor Flow, Lang Chain, etc.)
• Cloud AI services (Claude Code Azure OpenAI, AWS Bedrock, Vertex AI)
• Vector databases and modern data stack components
• Experience in a leadership role within the EPC or heavy construction space, specifically leading technology or digital transformation programs that impacted field operations, safety, and project controls
• Has demonstrated the ability to integrate AI systems with core ERP (JDE, Deltek), scheduling (Primavera P6/Microsoft Project), and BIM/CAD, PLS‑One systems
• Background in enterprise data architecture or digital transformation
• Understanding of change management and operational process improvement
• Degree in Computer Science, Engineering, Data Science, or…