• Serve as the technical lead for AI application development within the AI Foundry, setting standards for code quality, architecture, and delivery • Lead by doing: design and implement core AI application components, critical services, and integration layers • Mentor AI engineers; raise the bar on engineering rigor and AI-specific best practices • Establish quality thresholds and release criteria (accuracy, latency, reliability, cost, and user trust) • Design safeguards and “safe failure modes”: fallback behaviors, confidence thresholds, user controls, content filtering, and transparency patterns • Build AI-powered product capabilities end-to-end (service + workflow integration + instrumentation), including LLM-enabled workflows, RAG, summarization, classification, and automation patterns • Build and maintain shared libraries/components for AI application development (prompt/tooling patterns, service templates, evaluation utilities, safety layers) • Own technical readiness for production: reliability, observability, performance tuning, and incident response preparedness • Collaborate with platform Engineering and DevOps to ensure CI/CD and environment consistency, scaling strategies, cost controls for inference and secrets management and secure data handling • Partner tightly with AI product builders and workflow Product owners to translate validated prototypes into production implementations • Collaborate with core engineering teams to integrate AI capabilities into CentralReach’s main platforms • Identify and prioritize foundational investments that increase delivery velocity and reduce long-term maintenance: reusable components, platform primitives, and standardized patterns • Evaluate build vs. buy decisions for AI tooling and recommend approaches aligned to CR constraints • Stay current with AI application engineering practices and help translate emerging techniques into safe, valuable product capabilities

• Engage in rapid prototyping and planning specific to contexts in a cohort of up to 20 leadership teams. • Participate in monthly strategy calls and quarterly in-person intensives. • Interrogate fundamental beliefs about education's structure. • Leverage Playlab's platform to create custom AI tools that enhance human connectivity within education.

Are you a hands-on AI engineering leader with the vision to design enterprise-grade GenAI solutions-and the executive presence to influence business strategy at the highest levels? Ready to move beyond experimentation and build scalable, production-ready AI systems that drive measurable value across an organization? If you’re energized by turning frontier AI capabilities into real-world impact, this is your opportunity to lead and scale.   We are seeking a Director of AI Enablement to architect and deploy enterprise AI and GenAI solutions. Reporting directly to the Chief Technology Officer, you will partner with senior business executives, product leaders, and engineering teams to translate complex business requirements into scalable, secure, and high-performing AI applications. This role operates at the intersection of architecture, engineering, and strategy.   Builders Capital Exchange is one of the nation's largest private construction lender, offering cutting-edge financing solutions to developers and homebuilders. Our loan products include Acquisition, Development, Construction, and Bridge financing options-ranging from single-asset loans to portfolio loans and revolving credit facilities.   What You’ll Do: - Architect Enterprise AI Solutions - Design and deploy LLM-based, agentic, and applied machine learning systems that integrate seamlessly with enterprise data platforms and production environments. Build scalable, production-ready AI solutions that deliver measurable business outcomes. - Translate Strategy into Engineered Products - Partner directly with TD&O divisional leaders, product teams, and operations executives to convert high-impact business use cases into technical blueprints and deployed AI capabilities. - Lead Hands-On Engineering Execution - Guide teams in model development, fine-tuning, evaluation, and deployment. Ensure performance, observability, scalability, and compliance across AI systems operating in production environments. - Operationalize GenAI at Scale - Develop reusable frameworks, APIs, orchestration layers, and components that accelerate AI adoption across multiple product lines and business workflows. - Champion Responsible & Secure AI - Establish engineering standards for model governance, telemetry, version control, and risk management in partnership with Enterprise Architecture and governance teams. Ensure AI systems are secure, ethical, and compliant. - Build and Inspire High-Performance Teams - Lead cross-functional squads to prototype, iterate, and operationalize AI agents and cognitive capabilities. Foster a builder culture grounded in experimentation, accountability, and delivery. - Stay Ahead of the Frontier – Continuously evaluate emerging AI tools, frameworks, and architectural patterns. Identify opportunities to responsibly integrate cutting-edge capabilities into enterprise platforms.

• Champion AI-unlocked creativity: Build seamless AI-powered tools by obsessing over real workflow friction, and creating solutions that augment human creativity and effectiveness. • Drive AI transformation: Define the technical strategy for empowering our UX disciplines and workflows with AI. • Ship AI tools: Prototype, test, and deploy full-stack applications and plugins that solve real problems for working designers. • Model technical craft: Set a high standard for internal tool quality, user adoption, and workflow transformation. Seek feedback, embrace experimentation, and iterate to deliver exceptional web applications and AI integrations for complex, workflow-heavy experiences. • Build for workflow integration: Thrive in our collaborative, cross-functional environment with high ownership, partnering closely with Design, Research, Ops, and Engineering to maximize transformation impact. • Elevate AI fluency: Model technical curiosity, AI integration thinking, and systems perspective throughout the UX organization. Help teams become more effective collaborators with AI tools.