What are the responsibilities and job description for the Principal AI Agentic System Engineer position at Working at Signature Aviation?
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.
Qualifications:
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
Responsibilities:
• 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