Director of Artificial Intelligence
Grayson Search Partners, Chicago, IL, United States
AI ARCHITECT & ENGINEERING DIRECTOR
While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
Overview Hands-on technical leader responsible for designing, building, and scaling AI solutions across the business. This role combines deep Databricks expertise, modern AI platforms, and Microsoft’s AI ecosystem with the ability to turn real business problems into production-ready systems. You won’t just set strategy—you’ll build. This person operates as both the lead AI engineer and the driver of enterprise AI adoption across operations, development, leasing, and asset management.
Responsibilities Build & Deliver AI Solutions Design and deploy end-to-end ML solutions in Databricks (feature engineering, training, tuning, deployment, monitoring) Develop models across predictive analytics, forecasting, NLP, and generative AI Rapidly prototype, validate impact, and productionize solutions Integrate AI into enterprise systems (Yardi, Salesforce, ERP, BI, internal tools) Own AI Platforms & Architecture Lead development using Databricks (core), Microsoft Copilot Studio, and Azure AI services Determine when to use ML, generative AI, or automation Make key decisions on model selection, architecture, and scalability Drive AI Strategy Define and evolve a practical, execution-focused AI roadmap Identify high-impact use cases tied to cost savings, revenue growth, and efficiency Balance experimentation with production readiness Governance & Reliability Implement scalable AI governance (model versioning, monitoring, drift detection, security) Ensure solutions are explainable, auditable, and compliant Lead Execution Deliver AI products, tools, and automations end-to-end Manage vendors and external partners Build and lead a high-performing AI team Establish best practices, documentation, and adoption frameworks
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Qualifications 5+ years leading and delivering AI/ML solutions at scale Hands-on experience building ML models in Databricks Strong expertise in PySpark/Spark ML, Python ML frameworks, and full ML lifecycle Proven experience deploying AI into production environments Ability to translate business needs into technical solutions Bachelor’s degree in a technical field or equivalent experience
Nice to Have Microsoft Copilot Studio / Microsoft AI ecosystem experience Background in real estate, finance, or asset-heavy industries Experience with MLOps and CI/CD for data and ML
While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
Overview Hands-on technical leader responsible for designing, building, and scaling AI solutions across the business. This role combines deep Databricks expertise, modern AI platforms, and Microsoft’s AI ecosystem with the ability to turn real business problems into production-ready systems. You won’t just set strategy—you’ll build. This person operates as both the lead AI engineer and the driver of enterprise AI adoption across operations, development, leasing, and asset management.
Responsibilities Build & Deliver AI Solutions Design and deploy end-to-end ML solutions in Databricks (feature engineering, training, tuning, deployment, monitoring) Develop models across predictive analytics, forecasting, NLP, and generative AI Rapidly prototype, validate impact, and productionize solutions Integrate AI into enterprise systems (Yardi, Salesforce, ERP, BI, internal tools) Own AI Platforms & Architecture Lead development using Databricks (core), Microsoft Copilot Studio, and Azure AI services Determine when to use ML, generative AI, or automation Make key decisions on model selection, architecture, and scalability Drive AI Strategy Define and evolve a practical, execution-focused AI roadmap Identify high-impact use cases tied to cost savings, revenue growth, and efficiency Balance experimentation with production readiness Governance & Reliability Implement scalable AI governance (model versioning, monitoring, drift detection, security) Ensure solutions are explainable, auditable, and compliant Lead Execution Deliver AI products, tools, and automations end-to-end Manage vendors and external partners Build and lead a high-performing AI team Establish best practices, documentation, and adoption frameworks
xsgimln
Qualifications 5+ years leading and delivering AI/ML solutions at scale Hands-on experience building ML models in Databricks Strong expertise in PySpark/Spark ML, Python ML frameworks, and full ML lifecycle Proven experience deploying AI into production environments Ability to translate business needs into technical solutions Bachelor’s degree in a technical field or equivalent experience
Nice to Have Microsoft Copilot Studio / Microsoft AI ecosystem experience Background in real estate, finance, or asset-heavy industries Experience with MLOps and CI/CD for data and ML