Job 143225

Honeywell

Not specified (assumed to be hybrid or onsite based on industry standards).
Python apis using fastapi
Enterprise ai/ml platform services
Ci/cd stacks for edge deployment
Honeywell is seeking a Full Stack AI Platform Engineer to design and build AI systems that enhance automation across its global portfolio. The role requires extensive experience in software engineering and AI/ML operations, with a focus on developing scalable solutions for real-time data processing and model deployment

Job Summary

  • Design, build, and scale AI systems end-to-end — from high-throughput IoT streaming pipelines and knowledge graph infrastructure, through LLM orchestration and RAG services, to the React-based interfaces that surface autonomous insights to plant engineers, facility managers, and OT security analysts.
  • Work at the intersection of data engineering, machine learning operations, and edge AI — building production-grade infrastructure that processes billions of IoT events from building management systems, deploys models to edge devices, and enables AI-driven applications.
  • This is a high-impact individual contributor role for someone who thrives in ambiguity, ships production systems, and can operate across the full stack from cloud-native platforms to edge GPU hardware.

Matching Summary

Match Score: 85

Honeywell is seeking a Full Stack AI Platform Engineer to design and build AI systems that enhance automation across its global portfolio. The role requires extensive experience in software engineering and AI/ML operations, with a focus on developing scalable solutions for real-time data processing and model deployment.

Skills & Requirements

Must-have

  • Python APIs using FastAPI
  • Enterprise AI/ML platform services
  • CI/CD stacks for edge deployment
  • ML orchestration with LangGraph
  • AI workloads with ML-Ops
  • Edge AI on NVIDIA Jetson
  • Knowledge graphs and ontology engineering

Nice-to-have

  • Building management systems experience
  • Agile development environment
  • Fast-paced and dynamic environment

Key Requirements

  • 3 plus years of experience
  • Bachelor's degree in technical discipline
  • Proficiency in Python and systems language
  • Cloud-native data platforms experience
  • Production ML/AI pipelines experience
  • LLM application frameworks experience
  • Edge AI deployment experience

Work Rights

Not specified

Tailored Resume

Cover Letter