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Specialized LLM skills reduce applicant pool but senior ML role in a metro keeps competition medium.
Core ML/LLM skills are transferable, but renewable-energy domain knowledge adds moderate specificity.
Explicit 7–10 years requirement, mandatory LLM/RAG experience and demo request make screening highly strict.
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Develop and maintain production-grade generative AI systems including large language model (LLM) powered agents embedded into GreenPowerMonitor’s Horizon cloud platform.
Design and implement Retrieval-Augmented Generation (RAG) pipelines integrating diverse operational and metadata sources to provide actionable AI insights for renewable energy asset management.
Collaborate with product managers and software engineers to deploy AI solutions that enhance predictive maintenance and platform intelligence for global renewable energy professionals.
Bachelor’s or Master’s degree (or equivalent experience) in Mathematics, Data Science, Computer Science, Machine Learning, or related field.
7 to 10 years of total professional experience.
Hands-on experience with Large Language Models (LLMs) or generative AI systems including RAG pipelines, embeddings, prompt optimization, and understanding Transformer architectures.
Proficiency in Python; familiarity with CI/CD, Docker, Kubernetes, and Git is a plus.
Experienced engineer capable of taking cutting-edge LLM and agent-based AI systems from prototype to scalable production deployment in complex, data-rich environments.
Comfortable working cross-functionally to integrate AI solutions into existing cloud platforms targeting operational optimization for renewable energy.
Strong communicator able to clearly explain complex AI concepts to both technical and non-technical stakeholders.