AI Product Manager; Renewable Energy

The Company

Cypress Creek Renewables is powering a sustainable future, one project at a time. We develop, finance, own and operate utility-scale and distributed solar and storage projects across the country. Fostering a diverse group of innovative thinkers from all backgrounds, Cypress people are drawn to work in a purpose-driven organization. We hope you will join us.

CCReneew is seeking an experienced AI Product Manager / Engineer to drive the development and deployment of artificial intelligence and machine learning solutions across our solar project development lifecycle. This is a high-impact, cross-functional role sitting at the intersection of renewable energy domain expertise and advanced technology. Reporting directly to the Chief Technology Officer, you will own the product roadmap for AI-powered tools that streamline site selection, EPC procurement and management, interconnection analysis, and construction oversight.

The ideal candidate brings a rare combination of hands-on experience in solar development—including navigating EPC contracts, interconnection queues, and greenfield site assessment—and proven ability to translate complex business problems into scalable AI/ML products. You will partner closely with project development, engineering, and operations teams to identify high-value automation and intelligence opportunities, then lead end-to-end delivery.

• AI Product Strategy & Roadmap
• Define and own the AI product roadmap aligned with CCRenew’s solar development pipeline strategy and CTO vision.
• Identify opportunities to apply machine learning, computer vision, geospatial AI, and predictive analytics across the development lifecycle.
• Translate domain pain points in site selection, EPC management, interconnects, and construction into structured, prioritized product requirements.
• Build and maintain stakeholder alignment across development, engineering, finance, and legal teams.

• Lead development of AI-driven site screening and scoring tools that evaluate land availability, solar irradiance, transmission proximity, environmental constraints, and permitting risk.
• Integrate geospatial data sources (LiDAR, satellite imagery, GIS layers) into automated site analysis workflows.
• Build predictive models for site feasibility scoring that reduce manual assessment time and improve go/no-go decision quality.

• Develop AI tools to model and forecast interconnection queue positions, study timelines, and upgrade cost scenarios across MISO, PJM, CAISO, ERCOT, and other ISOs/RTOs.
• Build automated monitoring systems for regulatory queue changes, FERC Order compliance, and interconnection agreement milestones.
• Apply NLP and document intelligence to process study results, interconnection agreements, and utility correspondence at scale.

• Design AI-powered tools for EPC bid analysis, contract risk scoring, and subcontractor performance benchmarking.
• Develop cost estimation and variance prediction models informed by equipment pricing trends, labor markets, and project-specific variables.
• Automate review of EPC contracts, change orders, and scope documents using large language model (LLM) pipelines.

• Build AI solutions for real-time construction progress tracking using drone imagery, IoT sensor data, and project management integrations.
• Develop schedule risk and delay prediction models that surface issues early and recommend mitigation actions.
• Create automated reporting and alerting systems that consolidate field data, RFI logs, inspection records, and milestone tracking.

• Architect and, where required, directly engineer ML pipelines, data ingestion systems, and model deployment infrastructure.
• Partner with data engineering and software engineering to ensure production-grade reliability, scalability, and security of AI systems.
• Establish model monitoring, drift detection, and retraining workflows for deployed models.
• Evaluate and integrate third-party AI tools, APIs, and vendor platforms relevant to the solar development stack.

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