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At Signature Aviation, we are modernizing operations and customer experiences through advanced data platforms and artificial intelligence. We are seeking a Principal Engineer - AI Agentic Systems to design, architect, and implement next-generation AI systems that enable intelligent automation, predictive insights, and autonomous decision-making across the enterprise.

This role will lead the technical design of agentic AI systems that support initiatives such as dynamic pricing for revenue optimization, ramp capacity optimization, predictive revenue and operational forecasting, crew and CRM data enrichment, and automated task orchestration across operational teams. The Principal Engineer will partner closely with AI engineers, data scientists, platform teams, and operational leaders to deliver scalable AI capabilities that improve efficiency, decision-making, and operational performance across Signature's global network. 

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:

10-12+ years of experience in software engineering, distributed systems, or AI/ML platform development 
Demonstrated experience building and deploying production-grade LLM applications or agent-based AI systems 
Strong expertise in cloud-native architecture and scalable platform design 
Experience integrating AI systems with enterprise data and operational platforms 
Bachelor's degree in Computer Science, Engineering, or a related technical field (advanced degree preferred)

Additional knowledge and skills:

Experience with LLM application frameworks such as LangChain, LlamaIndex, or Semantic Kernel 
Experience integrating with foundation models such as OpenAI GPT, Claude, or LLaMA-based systems 
Knowledge of vector databases such as Pinecone, Weaviate, or Redis Vector 
Strong programming experience with Python and TypeScript 
Experience with enterprise AI platforms including Azure AI, AWS Bedrock, or Google Vertex AI 
Experience with model lifecycle management and MLOps platforms such as MLflow or Azure ML 
Familiarity with AI observability tools such as Langfuse or Weights & Biases 
Experience implementing enterprise authentication and security patterns such as OAuth2 and RBAC 
Familiarity with pricing optimization systems, operational analytics, or forecasting platforms 
Experience in aviation, logistics, mobility, or other large-scale operational environments preferred 

Architect scalable agentic AI systems that enable intelligent automation and decision support across enterprise operations

Design and implement AI solutions supporting dynamic pricing and revenue optimization initiatives

Develop predictive systems that improve ramp capacity planning, operational throughput, and workforce utilization

Engineer LLM-powered applications using retrieval-augmented generation (RAG), agent frameworks, and orchestration platforms

Design AI-driven automation solutions that streamline operational workflows and task management

Build and maintain pipelines that enrich enterprise datasets, including crew, customer, and CRM data platforms

Integrate AI capabilities with enterprise platforms and operational systems

Establish engineering standards and architectural patterns for AI and LLM-based application development

Ensure responsible AI implementation, including governance, monitoring, and security considerations

Provide technical leadership, architectural guidance, and mentorship to engineering teams building AI capabilities