AI Solutions Architect

Job Description

We are 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 the gap between business needs and technical implementation, focusing on rapid prototyping and scaling proof-of-concepts into production-ready systems. You will work closely with Engineering, Operations, Development, and business stakeholders to deliver AI solutions that enhance our 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, Modal, and cloud-native technologies.
• Develop rapid proof-of-concepts for Retrieval augmented generation (RAG) applications, operational optimization, process optimization, energy forecasting, predictive maintenance, and computer vision (drone footage) use cases.
• Design and implement AI agentic workflows using frameworks such as LangChain, LangGraph, CrewAI, or similar orchestration tools.
• Create interactive demos and prototypes using Gradio and Streamlit 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, renewable energy applications, including wind/solar forecasting, and asset performance optimization.
• Integrate AI capabilities via APIs and SDKs from providers including OpenAI, Anthropic, Azure OpenAI, and Hugging Face
• Implement MLOps pipelines using Dagster, Snowflake, Sentry, and Modal for model training, deployment, and monitoring.
• Design and optimize RAG architectures, including vector database implementation, embedding strategies, and retrieval pipelines.
• Ensure robust version control and collaboration practices using GitLab.

Production Scaling & Operations

• Lead the transition of successful prototypes to production-grade applications.
• Collaborate with DataOps and platform teams to ensure scalable, secure deployments.
• Implement monitoring, logging, and alerting AI systems in production.
• Establish best practices for AI model governance and compliance.

Stakeholder Engagement

• Conduct requirements gathering sessions with operations, trading, and executive teams.
• Present technical concepts and ROI analyses to both 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 degree in Computer Science, Engineering, Data Science, or related field
• 5+ years of experience in AI/ML solution architecture and implementation
• Proven track record of taking AI projects from proof-of-concept to production.
• Strong experience with Snowflake Cortex AI or similar systems for enterprise AI workflows
• Hands-on experience with AI agentic frameworks (LangChain, LangGraph, Semantic Kernel, CrewAI, or AutoGen) for building autonomous AI workflows.
• Proficiency in integrating LLM APIs and SDKs (OpenAI, Anthropic, Azure OpenAI, Hugging Face) into production applications.
• Experience designing and implementing RAG systems, including vector databases (Pinecone, Weaviate, Chroma, pgvector, or similar), embedding models, and retrieval optimization.
• Experience building interactive applications with Gradio and Streamlit
• Advanced GitHub/GitLab workflows including CI/CD, branching strategies, and code review processes.
• Expertise in Python, SQL, and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies
• Strong understanding of data engineering principles, ETL processes, and data governance

Essential Skills

• Deep knowledge of machine learning algorithms, particularly time series forecasting and predictive analytics.
• Strong prompt engineering skills with experience optimizing LLM performance and implementing function calling/tool use patterns.
• Understanding of distributed systems, microservices architecture, and API design
• Knowledge of data security, privacy, and compliance requirements
• Ability to evaluate and benchmark AI/LLM solutions for accuracy, latency, and cost optimization.

What Would Be Nice

• Experience in renewable energy, utilities, or energy trading sectors
• Experience with advanced AI techniques, such as computer vision for asset monitoring, and AI evaluation frameworks
• Familiarity with energy management systems (EMS), SCADA, and industrial IoT platforms
• Experience with energy sector data (weather, generation, market pricing)
• Knowledge of energy markets, grid operations, and regulatory frameworks
• Proficiency with Modal for scalable ML model deployment and orchestration
• Certifications in Snowflake, cloud platforms, or energy industry standards

Clearway will not sponsor non-immigrant visas for this position (H-1B, TN, E-3, etc.).