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

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)
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

Principal AI Agentic System Engineer

Key skills