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Tier-1 brand, metro locations, in-demand AI role, and broad skillset requirements increase candidate competition.
Strong preference for AI applied within engineering, manufacturing, or energy makes cross-industry transfer harder.
Role demands specific AI implementation and engineering-domain experience but lacks explicit years requirement.
Own identification, design, deployment, and sustainment of AI solutions improving engineering productivity, quality, speed, and outcomes within a Wind Engineering subsystem.
Translate business and technical challenges into prioritized AI use cases with measurable success criteria and maintain a subsystem AI opportunity roadmap.
Integrate AI into engineering workflows, ensure compliance with governance and quality standards, and drive AI adoption and capability development within the subsystem.
Bachelor's degree in Engineering, Computer Science, Data Science, Applied Mathematics, Systems Engineering, or related technical discipline.
Experience designing, developing, deploying, or supporting AI, machine learning, advanced analytics, automation, or digital engineering solutions.
Working knowledge of modern AI technologies including generative AI, retrieval-augmented generation, AI agents, machine learning, and workflow automation.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced applying AI solutions in engineering, manufacturing, industrial, energy, or highly technical environments, especially Wind Engineering.
Comfortable operating in a matrixed environment collaborating with subsystem leadership, senior AI architects, engineers, and product/process owners.
Skilled in balancing innovation with engineering rigor, governance, and quality requirements while driving adoption and sustained AI solution impact.