Director of AI Enablement

Director of AI Enablement at Builders Capital

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.

About Builders Capital

Builders Capital Exchange is one of the nation's largest private construction lenders, 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.

Requirements

What We're Looking For:

• Proven AI Engineering Expertise: Demonstrated success designing, deploying, and maintaining AI or GenAI systems in production environments, including LLM-based solutions, agentic architectures, RAG pipelines, or advanced ML systems.
• Engineering Leadership Experience: 10+ years leading product, platform, or applied AI engineering teams in high-scale environments (cloud, SaaS, fintech, or large enterprise systems).
• Architectural Fluency: Deep expertise in modern AI infrastructure, including vector databases, orchestration frameworks, MLOps/DevOps integration, and enterprise-grade system design.
• Business Translation Capability: Ability to engage directly with senior executives and convert strategic objectives into technical execution plans and working AI systems.
• Executive Presence & Influence: Comfortable advising CIO-level leaders and product executives, articulating AI’s value in business terms, and building trust across technical and non-technical stakeholders.
• Education: Bachelor’s degree in Computer Science, Engineering, Data Science, or related technical field (advanced degrees preferred) or equivalent experience.
• Experience at a technology or product company leading AI platform or applied ML development at scale.
• Hands-on experience with enterprise AI frameworks such as Azure OpenAI, AWS Bedrock, LangChain, AutoGen, CrewAI, or similar.
• Demonstrated success establishing AI engineering standards, reusable frameworks, or AI Centers of Excellence.
• Experience delivering GenAI applications supporting customer engagement, operations, or risk functions in complex organizations.
• Industry leadership through publications, conference presentations, or open-source contributions.

Benefits

• Innovative Environment: Join a forward-thinking company at the forefront of the construction finance industry with access to cutting-edge technology and resources.
• Work Flexibility: Enjoy a flexible work environment where you can balance team leadership with your personal life.
• National Impact: Be part of a nationwide operation that’s shaping the future of construction financing and making a difference for builders, developers, and homeowners across the U.S.
• Health Insurance: Builders Capital pays 100% of your medical insurance premiums to keep you healthy and stress-free, offering PPO and HSA plans.
• Competitive Compensation: We offer competitive wages that reward your expertise and hard work.
• Paid Time Off: Take time to recharge with 3 weeks of paid time off each year.
• Paid Holidays: Enjoy 10 paid holidays throughout the year so you can spend quality time with family, friends, or doing whatever you love.

We’re building more than AI systems—we’re building the foundation for responsible, scalable enterprise intelligence. If you’re ready to architect what’s next and enable AI at scale, we want to hear from you. We are an Equal Opportunity Employer (EEO) and welcome all qualified applicants. This is a full-time, exempt position. This job description is not intended to be a comprehensive list of all duties and responsibilities and may change as business needs evolve.

Key skills/competency

• AI Architecture
• Generative AI
• Machine Learning
• LLM Deployment
• MLOps
• Engineering Leadership
• Enterprise AI Solutions
• Data Platforms
• AI Governance
• Business Strategy