Chief AI Architect (Head of AI Engineering & Architecture)
Department: Information Technology / Digital Transformation
Reports To: CIO / Executive Leadership
About Virginia Transformer
Virginia Transformer Corporation is the largest U.S.-owned manufacturer of power transformers, serving electric utilities, industrial, renewable energy, and commercial customers across North America. With over 50 years of experience and multiple manufacturing facilities, VTC is a technology-driven company focused on engineering excellence, operational performance, and supporting critical infrastructure.
On the heels of achieving 3X growth, we are building the team to support our next phase of expansion. This is an opportunity to lead cutting-edge innovation and shape the future of AI-driven operations within a high-impact industrial organization.
About the Role
Virginia Transformer is seeking a highly technical and visionary Chief AI Architect (Head of AI Engineering & Architecture) to lead the development of enterprise-wide AI capabilities.
This role will own the AI architecture, platforms, and technical strategy—ensuring scalable, secure, and high-performing AI systems that integrate seamlessly with core enterprise platforms such as ERP, CRM, PLM/PDM, and MES systems.
This is a hands-on leadership role requiring deep technical expertise in modern AI frameworks, data architecture, and distributed systems, with a strong focus on building enterprise-grade solutions.
Key Responsibilities
AI Architecture & Strategy
- Define and own the end-to-end AI architecture across the enterprise (data → models → orchestration → applications).
- Establish engineering standards for AI development, including RAG architectures, LLM integration, embeddings, and model lifecycle management.
- Design scalable and secure AI systems aligned with business and operational needs.
Data & Infrastructure Design
- Architect and implement scalable data pipelines and AI infrastructure, with a focus on Azure-based ecosystems.
- Ensure efficient data flow, storage, and processing across structured and unstructured data sources.
- Drive best practices for data governance, security, and performance.
AI Engineering & Platform Development
- Lead the development of reusable AI components, frameworks, and enterprise platforms.
- Guide the implementation of AI solutions that can scale across functions including operations, finance, supply chain, and engineering.
- Ensure modular, maintainable, and high-performance system design.
MLOps / LLMOps & Lifecycle Management
- Establish robust MLOps and LLMOps practices, including deployment, monitoring, versioning, and performance tracking.
- Implement processes for continuous improvement, retraining, and model optimization.
- Ensure reliability, traceability, and governance of AI systems.
Integration & Enterprise Systems Alignment
- Ensure seamless integration of AI solutions with enterprise platforms including ERP, CRM, MES, and PLM systems.
- Design API-driven and microservices-based architectures to support interoperability and scalability.
- Align AI initiatives with business processes and enterprise system capabilities.
Technology Evaluation & Innovation
- Evaluate and select AI tools, frameworks, and platforms aligned with enterprise strategy.
- Stay current with advancements in AI, LLMs, and data engineering to drive innovation.
- Lead experimentation and pilot initiatives for new AI capabilities.
Leadership & Technical Guidance
- Provide technical leadership and architectural direction to internal engineering teams and external vendors.
- Establish best practices, coding standards, and architectural governance.
- Mentor engineers and build internal AI engineering capability.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Data Science, or related field required; advanced degree preferred.
- 10–15+ years of experience in software engineering, data engineering, or AI/ML, with significant experience in architecture roles.
- Strong hands-on experience with AI/ML systems, LLMs, and modern AI frameworks.
- Deep expertise in data architecture, distributed systems, and scalable infrastructure design.
- Experience with Azure AI, Data Lake, and cloud-based data platforms.
- Strong knowledge of APIs, microservices, and orchestration frameworks.
- Familiarity with enterprise systems (ERP, MES, PLM) and their integration patterns.
- Proven ability to design enterprise-grade systems—not just build models.
Preferred Skills
- Experience implementing RAG-based architectures and enterprise LLM applications.
- Strong understanding of data pipelines, feature engineering, and real-time processing systems.
- Exposure to manufacturing or industrial environments is a plus.
- Experience leading enterprise AI transformation initiatives.
Leadership Profile
- Deeply technical leader with strong architectural vision and execution capability.
- Hands-on, solution-oriented, and able to operate in a fast-paced, evolving environment.
- Strong decision-maker with a focus on scalability, reliability, and business impact.
- Ability to bridge technical architecture with business strategy and operational execution.
Why Join Virginia Transformer
- Lead enterprise AI transformation in a high-growth industrial organization.
- Build and scale cutting-edge AI capabilities with real-world operational impact.
- High-visibility leadership role with direct influence on business strategy.
- Competitive compensation and long-term growth opportunity.
