Honeywell is seeking a Senior Advanced AI Engineer to design and deliver AI solutions across classic ML, GenAI, and agentic systems. You will build production-grade AI services, including RAG pipelines, embedding APIs, retrieval endpoints, and guardrails for safety and compliance. The role involves developing agent tool adapters, integration layers, and secure APIs to enable AI agents to safely perform actions, along with implementing policies for PII protection and content moderation. You will create event-driven and asynchronous services using AWS-native capabilities, and develop microservices and SDKs to support scalable, low-latency interactions between AI models, vector databases, and enterprise systems. You will collaborate with AI Architects, Platform Engineers, MLOps, Data Engineers, and Data Scientists to ensure reliability, security, observability, and alignment with best practices. Strong testing frameworks for AI-driven services, including regression and guardrail tests, will be part of the role, as will participation in code reviews and architectural discussions to improve AI-powered applications. This position is based in Phoenix, AZ or Charlotte, NC on a hybrid schedule.

Honeywell is seeking a Senior Advanced AI Engineer to design and deliver AI solutions across classic ML, GenAI, and agentic systems. You will build production-grade AI services, including RAG pipelines, embedding APIs, retrieval endpoints, and guardrails for safety and compliance. The role involves developing agent tool adapters, integration layers, and secure APIs to enable AI agents to safely perform actions, along with implementing policies for PII protection and content moderation. You will create event-driven and asynchronous services using AWS-native capabilities, and develop microservices and SDKs to support scalable, low-latency interactions between AI models, vector databases, and enterprise systems. You will collaborate with AI Architects, Platform Engineers, MLOps, Data Engineers, and Data Scientists to ensure reliability, security, observability, and alignment with best practices. Strong testing frameworks for AI-driven services, including regression and guardrail tests, will be part of the role, as will participation in code reviews and architectural discussions to improve AI-powered applications. This position is based in Phoenix, AZ or Charlotte, NC on a hybrid schedule.