Energy Digital Architect
6 - 10 years
United States
$140k - $180k/year
Full-time
Remote
1 month ago
About the role
The Role: As an Energy Digitalization Architect, you will be the technical driving force behind the company's "Autonomous Energy Network" strategy. You will not only be responsible for designing complex digital architectures, but also for deeply integrating the decision-making capabilities of AI Agents into traditional power grids and new energy infrastructure. This is a key mid-level position that involves restructuring the logic of energy flow from scratch.
Key Responsibilities:
Architectural Restructuring: Designing digital transformations of traditional power grids using algorithms to upgrade the energy network from "passive transmission" to "proactive intelligent response."
AI Decision Integration: Introducing large-scale token processing capabilities and intelligent agents (AI Agents) into energy dispatching to achieve "fully automated flow" and precise dispatch of electricity between cities.
Automated Maintenance System Design: Leading the technical architecture of autonomous maintenance solutions using robots and drones, enabling fault prediction, automatic repair, and 24/7 unmanned operation of power plants through AI.
Technology Implementation and Management: As a mid-level backbone, leading the engineering team to transform complex algorithms into deliverable industrial-grade energy applications, coordinating the interface between algorithm development and physical power systems.
Strategic Optimization: In conjunction with the deployment of intelligent computing infrastructure, assess the efficiency of computing resources in supporting complex energy algorithms and optimize the performance of the "digital foundation."
Qualifications:Education: Master's or Doctoral degree in Computer Science, Power System Automation, Energy Engineering, or a related field.
Core Experience:
Over 10 years of experience in energy digitalization or smart grid architecture design.
Practical experience in distributed energy resources (DER), energy storage systems, or energy management systems (EMS).
Technical Skills:
Deep understanding of the application logic of artificial intelligence (especially LLM/AI Agents) in industrial or financial decision-making.
Familiarity with cloud-native architecture, large-scale data processing, and Industrial Internet of Things (IIoT) protocols.
Cross-Industry Thinking: Possesses a cross-industry perspective on "AI + Energy," and understands the role of inference cost reduction in restructuring the industry value chain.
Soft Skills: Strong logical decomposition ability and mid-level management experience; able to independently lead a team and report directly to senior management.
What We Offer: Deep involvement in the global strategic deployment of semiconductor and intelligent computing infrastructure. Work in a highly flattened, trust-based environment.
Take cutting-edge AI technologies to the real economy and transform energy, creating tangible social value.
Key Responsibilities:
Architectural Restructuring: Designing digital transformations of traditional power grids using algorithms to upgrade the energy network from "passive transmission" to "proactive intelligent response."
AI Decision Integration: Introducing large-scale token processing capabilities and intelligent agents (AI Agents) into energy dispatching to achieve "fully automated flow" and precise dispatch of electricity between cities.
Automated Maintenance System Design: Leading the technical architecture of autonomous maintenance solutions using robots and drones, enabling fault prediction, automatic repair, and 24/7 unmanned operation of power plants through AI.
Technology Implementation and Management: As a mid-level backbone, leading the engineering team to transform complex algorithms into deliverable industrial-grade energy applications, coordinating the interface between algorithm development and physical power systems.
Strategic Optimization: In conjunction with the deployment of intelligent computing infrastructure, assess the efficiency of computing resources in supporting complex energy algorithms and optimize the performance of the "digital foundation."
Qualifications:Education: Master's or Doctoral degree in Computer Science, Power System Automation, Energy Engineering, or a related field.
Core Experience:
Over 10 years of experience in energy digitalization or smart grid architecture design.
Practical experience in distributed energy resources (DER), energy storage systems, or energy management systems (EMS).
Technical Skills:
Deep understanding of the application logic of artificial intelligence (especially LLM/AI Agents) in industrial or financial decision-making.
Familiarity with cloud-native architecture, large-scale data processing, and Industrial Internet of Things (IIoT) protocols.
Cross-Industry Thinking: Possesses a cross-industry perspective on "AI + Energy," and understands the role of inference cost reduction in restructuring the industry value chain.
Soft Skills: Strong logical decomposition ability and mid-level management experience; able to independently lead a team and report directly to senior management.
What We Offer: Deep involvement in the global strategic deployment of semiconductor and intelligent computing infrastructure. Work in a highly flattened, trust-based environment.
Take cutting-edge AI technologies to the real economy and transform energy, creating tangible social value.