MISO is hiring an AI Data Architect to build secure, scalable AI platforms in the Microsoft Azure ecosystem to drive real-time analytics, predictive maintenance, grid optimization, and market operations within the energy industry.
Requirements
- Proven expertise with the Azure ecosystem, including Azure ML, Synapse, Data Factory, Data Lake, Cognitive Services, and Azure OpenAI, plus hands-on experience with MLOps tools like MLflow and Azure DevOps.
- Designing secure, scalable solutions using data modeling, ETL processes, data warehousing, APIs, and event/stream processing.
- Proficiency in Python, R, SQL, and experience with tools like Power BI, Tableau, or Azure Analysis Services.
- Deep understanding of cloud-native design (IaaS, PaaS, SaaS), along with CI/CD automation for data and AI solutions.
- Ability to align AI adoption with business goals, mentor teams, communicate complex ideas clearly, and stay ahead of AI/ML, cloud, and energy system trends.
- 8+ years in data/AI roles, including 3+ years in architecture.
Responsibilities
- Integrate AI capabilities into energy trading systems, grid management tools, asset monitoring platforms, and market analytics dashboards.
- Lead proof-of-concept initiatives for emerging AI technologies and their application to energy operations.
- Partner with data scientists and engineers to implement ML models with MLOps best practices in Azure.
- Work side by side with Enterprise Architecture to ensure every solution aligns with the company’s long-term strategy and technology roadmap.
- Propose new solutions that can serve multiple teams, while documenting the “why” behind architectural choices so everyone is aligned.
- Communicate across all levels of the organization, lead critical discussions on cost and technology tradeoffs, and champion continuous improvement.
Other
- Mentor business teams, partners, and domain experts while setting clear frameworks, guardrails, and accelerators that make delivery smoother and faster.
- Communicate across all levels of the organization, lead critical discussions on cost and technology tradeoffs, and champion continuous improvement.
- Ability to align AI adoption with business goals, mentor teams, communicate complex ideas clearly, and stay ahead of AI/ML, cloud, and energy system trends.
- Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or related field.
- Hybrid work environment
