About the role
Roles and Responsibilities:
- Architectural Leadership: Lead the design, implementation, and validation of AI-ready platform lifecycle tools, scalability and deployment of predictive and generative AI models.
- Infrastructure Design: Define complex network architectures and hardware/software configurations that support both on-prem edge computing and cloud-based AI workloads.
- System Hardening: Make the system ready for Installation, configuration, patching, and hardening to ensure the highest levels of cybersecurity of assets.
- Cross-Functional Collaboration: Interface with cross functional team including Principal Engineers, Product Line Managers to translate business needs into technical AI requirements, maintaining delivery plans using Agile methodologies.
- Global Project Coordination: Drive and coordinate multiple AI-driven programs simultaneously across a global, cross-functional environment, ensuring alignment between manufacturing, sourcing, and suppliers.
- Continuous Improvement: Implement Lean process methodologies to optimize the AI development lifecycle, from data ingestion at the controller level to model inference at the HMI.
- Support & Deployment: Provide high-level technical support to field personnel during the deployment of AI-enhanced control systems and HMI platforms.
Required Skills:
- 12-15 years of relevant experience on the industrial control systems, platform architecture and Gen AI
- Industrial Control Systems: Deep knowledge of MarkVIe controller platforms, ToolboxST, and HMI platform architecture.
- AI/ML Architecture: Proven experience in designing scalable AI solutions, including knowledge of model deployment, data orchestration, and MLOps.
- Network & Security Engineering: Expertise in routers, firewalls, switches, compute, and storage, specifically within Software-Defined Networks (SDN) and Active Directory environments.
- Compliance & Cybersecurity: Hands-on application of cybersecurity technologies and standards, with a firm awareness of NERC/CIP and IEC 62443 requirements for power generation.
- Virtualization & Cloud: Advanced proficiency in virtualization platforms, and integration of on-prem infrastructure.
- Agile Leadership: Experience leading technical teams and managing complex delivery roadmaps in an Agile framework.
Desired Skills:
- Scripting & Automation: Proficiency in scripting tools (Python, PowerShell, or Bash) to automate the deployment and monitoring of AI models.
- GenAI & Data Strategy: Familiarity with Large Language Models (LLMs), Vector Databases, and Retrieval-Augmented Generation (RAG) within an industrial context.
- Strategic Thinking: Ability to influence stakeholders by connecting AI technical capabilities for operational efficiency.
- Domain Expertise: Understanding of GT, ST, HRSG operations, and power plant operation and maintenance.
Relocation Assistance Provided: Yes