AI Solutions Architect
Clearwayjobs · Scottsdale, Arizona, United States
About this role
**AI Solutions Architect** **Location:** Scottsdale, AZ *(#LI-Hybrid)* ## What the Role Is We’re seeking an experienced **AI Solutions Architect** to join our data team and drive the development and deployment of **AI-powered solutions** that optimize renewable energy asset development and operations. This role bridges business needs and technical implementation—moving from **rapid prototyping** and **proofs-of-concept** to **production-ready systems**. You’ll partner with **Engineering, Operations, Development, and business stakeholders** to deliver AI solutions that enhance renewable power generation capabilities and optimize internal work processes. ## What You’ll Be Doing ### Solution Design & Development - Design and architect end-to-end AI solutions using **Snowflake Cortex AI** and cloud-native technologies. - Build rapid proofs-of-concept for **RAG**, operational/process optimization, energy forecasting, and predictive maintenance. - Design and implement **agentic workflows** using **LangChain, LangGraph, CrewAI**, or similar orchestration tools. - Create interactive demos/prototypes using **Streamlit** or **React** for stakeholder validation. - Translate business requirements into technical specifications and system architectures. ### Technical Implementation - Build and deploy scalable AI/ML models for business process optimization and renewable energy use cases (wind/solar forecasting, asset performance optimization). - Integrate AI capabilities via APIs/SDKs from **OpenAI, Anthropic, Microsoft Foundry, Hugging Face**, and others. - Implement **MLOps pipelines** using **Dagster**, **Snowflake**, and LLM observability tooling (e.g., **LangSmith** or **Langfuse**) for training, deployment, and monitoring. - Design and optimize **RAG architectures** (vector databases, embedding strategies, retrieval pipelines). - Ensure robust version control and collaboration using **GitHub/GitLab**. ### Production Scaling & Operations - Lead the transition of successful prototypes into production-grade applications. - Collaborate with **DataOps** and platform teams to ensure scalable, secure deployments. - Implement monitoring, logging, and alerting for AI systems in production. - Establish best practices for AI model governance and compliance. ### Stakeholder Engagement - Run requirements gathering sessions with operations and executive teams. - Present technical concepts and **ROI analyses** to technical and non-technical stakeholders. - Provide training and support to end users on AI-powered tools and dashboards. ## What You’ll Bring ### Required - Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field (or equivalent practical experience). - **5+ years** experience in ML/data engineering, including recent production **LLM/RAG** work. - Proven track record taking AI projects from **POC to production**. - Strong experience with **Snowflake Cortex AI** (or similar enterprise AI systems). - Hands-on experience with AI agentic frameworks (**LangChain, LangGraph, Microsoft Agent Framework, CrewAI**, or similar). - Hands-on experience with **Model Context Protocol (MCP)** for connecting agents to tools and data sources. - Proficiency integrating **LLM APIs/SDKs** (OpenAI, Anthropic, Azure OpenAI, Hugging Face) into production applications. - Experience designing/implementing **RAG systems** (vector databases like Pinecone/Weaviate/Chroma/pgvector/Snowflake vector search, embedding models, retrieval optimiza
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