Vector Databases Jobs in Orlando, FL (NOW HIRING)

At Signature Aviation, we are building an enterprise AI platform to transform operational efficiency, revenue optimization, and decision intelligence across our global network. This role will define and lead the strategy, architecture, and engineering delivery of AI capabilities that power dynamic pricing, ramp capacity optimization, predictive operations, CRM intelligence, and automated operational workflows. The Director, AI Agents & Platform Engineering will partner closely with Product, Commercial, Operations, and Technology leaders to scale AI solutions that directly impact revenue growth, operational performance, and customer experience.

This leader will build and guide high-performing AI engineering teams while establishing the governance, architecture, and platform capabilities required to deploy AI safely and effectively across the enterprise.
 

With more than 225 locations worldwide, Signature Aviation is the largest global network of private aviation terminals, delivering safe, convenient, and elevated experiences to those we serve. As a premier hospitality organization and a certified Great Place to Work, we are committed to redefining private air travel. Our nearly 6,000-strong team of aviation experts and enthusiasts is dedicated to delivering excellence to our guests and communities, and it starts with taking care of our team. Signature provides a variety of benefits, programs, and resources to support our team members' overall well-being and professional development. We proudly volunteer and give back, focusing on elevating the neighborhoods where we operate, empowering the next generation of aviation professionals, and supporting our veterans. 

From your health to your financial wellness, there are several benefits for you and your family when joining Signature Aviation.

     Our Benefits:

• Medical/prescription drug, dental, and vision Insurance
• Health Savings Account
• Flexible Spending Accounts
• Life Insurance
• Disability Insurance
• 401(k)
• Critical Illness, Hospital Indemnity and Accident Insurance
• Identity Theft and Legal Services
• Paid time off
• Paid Maternity Leave
• Tuition reimbursement 
• Training and Development
• Employee Assistance Program (EAP) & Perks

Minimum Education and/or Experience:

• 12-15+ years of experience in software engineering, AI/ML platforms, or data systems
• 7+ years leading engineering teams delivering complex distributed systems or enterprise AI platforms
• Demonstrated experience building and scaling AI or machine learning platforms in production environments.
• Experience leading cross-functional initiatives across engineering, product, and business stakeholders
• Bachelor's degree in Computer Science, Engineering, or a related technical field (advanced degree preferred)

Additional knowledge and skills:

• Experience with enterprise AI platforms such as Azure AI, AWS Bedrock, or Google Vertex AI
• Experience building LLM-enabled applications using frameworks such as LangChain or Semantic Kernel
• Knowledge of vector databases and retrieval-augmented generation architectures
• Strong proficiency in Python and distributed systems development
• Experience operating containerized platforms using Kubernetes and CI/CD pipelines
• Familiarity with AI monitoring, model lifecycle management, and MLOps platforms
• Experience designing AI systems supporting revenue optimization, pricing intelligence, or operational forecasting
• Experience in aviation, logistics, mobility, or other large-scale operational environments preferred

• Define and lead the enterprise AI platform strategy supporting revenue optimization, operations intelligence, and automation initiatives
• Build and lead high-performing AI engineering teams responsible for developing and scaling AI capabilities across the enterprise
• Drive the design and deployment of AI solutions enabling dynamic pricing, revenue optimization, and demand forecasting
• Lead development of predictive operational models to optimize ramp capacity, staffing, and operational throughput
• Establish enterprise data and AI architecture supporting scalable model deployment, orchestration, and monitoring
• Advance AI-driven data enrichment across CRM, crew, and operational data platforms
• Implement intelligent task orchestration and automation capabilities that improve operational efficiency across locations
• Establish governance frameworks for responsible AI, security, and model lifecycle management
• Partner with Product, Commercial, Operations, and Technology leadership to align AI capabilities with strategic business priorities
• Evaluate emerging AI technologies and platforms to continuously improve enterprise AI capabilities
• Communicate strategy, progress, and measurable business impact to executive leadership