Director, AI Architect&Engineer, Washington

AI Architect&Engineering Director

Core Spaces (Core) is more than a real estate company; it's a people company. Where building relationships is just as important as building properties. From researchers and architects to designers and operators, Core is made up of risk takers and dreamers who are on a mission to invent the future of living. Our six cultural values guide us every day and we strive to live them in everything we do: PUSH (Invent Better Places to Live), GRIT (We Got This), LIFT (Help Each Other Win), SHINE (Bring Your Full Self), UPHOLD (Never Break Trust), GROW (Always Get Better). Everything Core does stem from this culture of collaboration and innovation, and the drive to constantly improve the resident experience. This unique approach has led to creating spaces and services that are redefining the way people live.Founded in 2010, Core is a vertically integrated real estate investment manager focused on acquiring, developing and managing across the student housing and build-to-rent ("BTR") sectors. Its residential communities feature world-class amenities, progressive design, and hospitality-driven service. Core's student housing portfolio includes over 74,440 beds currently owned or managed, with a pipeline of over 53,860 beds in various stages of development. Core's BTR division has over 3,000 homes under development, now leasing or in its pipeline in high-growth metros nationwide.The AI Architect&Engineering Director is a hands-on technical leader responsible for designing, building, and deploying artificial intelligence solutions across the organization. This role blends deep practical experience with Databricks-based machine learning, modern AI platforms, and Microsoft's AI ecosystem, with the ability to translate business needs into working, production-grade systems.This is not solely an advisory role. The ideal candidate actively architects, prototypes, and implements AI solutions, while also shaping long-term strategy, governance, and adoption. They will serve as both the principal AI engineer and the strategic leader defining how AI is responsibly applied across operations, development, leasing, and asset management.What You Will Do

Hands-On AI Architecture&Development Design, build, and maintain end-to-end AI solutions using Databricks, including: Feature engineering pipelines ML model training, evaluation, and tuning Model deployment and monitoring in production Develop machine learning models directly in Databricks (e.g., predictive models, classification, forecasting, NLP, and applied generative AI use cases)Leverage Databricks AI capabilities (MLflow model registry, feature stores, notebooks, jobs, and orchestration) Build and integrate AI solutions with existing enterprise systems (Yardi, Salesforce, ERP, BI platforms, internal applications) Prototype quickly, validate value, and harden solutions for production useAI Platforms&Tooling Design and implement AI solutions using: Databricks (core requirement) Microsoft Copilot Studio and related Microsoft AI services Azure-native data and AI services where appropriate Evaluate when to use traditional ML vs. generative AI vs. automation Own the technical decisions around model selection, architecture, and scalabilityAI Strategy Define and maintain the enterprise AI roadmap based on what can be realistically built and supported Identify high-value, practical AI use cases tied to measurable business outcomes (cost reduction, revenue lift, operational efficiency) Balance experimentation with production readinessGovernance, Reliability&Responsible AI Implement practical AI governance that does not slow delivery, including: Model versioning and lineage Performance monitoring and drift detection Data privacy and security controls Ensure AI systems are explainable, auditable, and aligned with internal standards Execution&Delivery Oversee the development and deployment of AI products, tools, and automations Manage vendor relationships with AI platforms, cloud providers, and consulting partners Build and lead a high-performing AI team (engineers, data scientists, analysts) Create documentation, playbooks, and best practices for AI adoption across the companyOccasional travel may be necessary as needed Perform all other duties and tasks as assigned by management Must be able to complete all physical requirements of this role with or without a reasonable accommodation Ideally, You'll Have

5+ years in a senior leadership role designing and deploying AI systems at scale Proven, hands-on experience building ML models in Databricks (not just managing teams that do) Deep experience with PySpark/Spark ML, modern Python ML frameworks, and end-to-end ML lifecycle management, from model training through deployment and ongoing monitoringExperience integrating ML/AI solutions into production systems Experience translating business problems into technical solutions and back again Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field required, or equivalent practical experience You'll crush it if you have experience with:Microsoft Copilot Studio or Microsoft AI tooling Applying AI in real estate, finance, operations, or asset-heavy industries Machine Learning Ops patterns and CI/CD for data and ML workloads Reports to: Vice President, Data Strategy As an Equal Opportunity Employer, Core Spaces celebrates diversity and is committed to creating an equitable and inclusive environment, which creates a sense of belonging for all employees. We do not discriminate and believe every individual should be proud of who they are and the community they represent.Pay Range: USD $205,000.00 - USD $215,000.00 /Yr. Additional Compensation: Employees may be eligible for discretionary bonuses, typically up to 20% of base salary annually, depending on individual and organizational performance. The compensation range listed reflects the base salary or hourly rate that we reasonably and in good faith expect to offer for this role at the time of posting. Actual compensation may vary based on factors such as education, experience, skills, certifications, seniority, geographic location, and business needs.