We are seeking a Full Stack AI Platform Engineer to join our Data Engineering, AI & ML Platform team. This role is central to designing, building, and scaling the enterprise AI/ML platform that powers intelligent automation across a global portfolio.
As a Full Stack AI Platform Engineer here at Honeywell, you will 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.
You will 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 including predictive diagnostics, energy monitoring, and RAG-based knowledge systems.
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. You will report to our Sr Data Engineering Manager and work from our Atlanta, GA location on a hybrid basis.
- Note: for the first 90 days, new hires must be prepared to work onsite 100% M-F.
KEY RESPONSIBILITIES
AI/ML Platform Engineering
- Develop high-performance, production-ready Python APIs using FastAPI to serve as the primary interface for on-device model inference
- Design, build, and maintain enterprise AI/ML platform services on multi-cloud infrastructure including model deployment, serving and experiment tracking.
- Build robust CI/CD stacks to automate the testing of inference logic and the deployment of API services to edge devices.
- Implement ML orchestration workflows using LangGraph, MLflow, and custom orchestration layers for multi-agent AI systems.
- Develop and integrate AI workloads using ML-Ops and tracing tools like LangSmith.
- Design and implement automated data processing pipelines within FastAPI to handle real-time sensor or image inputs for the model.
- Bridge the gap between research and deployment by converting code from experimental into modular, maintainable Python packages.
Edge AI & Inference
- Ability to integrate and run pre-built AI models on local hardware using standard industry runtimes.
- Skilled at building the software logic required to process data inputs and handle model outputs efficiently.
- Expert at developing Python-based services and automating their deployment to devices via standardized pipelines.
- Capable of monitoring and optimizing software to run reliably within strict memory and hardware limitations.
- Experience deploying containerized models from Azure to edge devices using Azure IoT Edge or managed online endpoints
Data & Knowledge Engineering
- Experience building pipelines to structure, clean, and store data for model training or real-time retrieval (RAG) on edge devices
- Ability to convert experimental data processing logic from notebooks into production-ready Python modules.
- Design automated workflows to collect, label, and manage datasets, ensuring high-quality data is available for continuous model improvement.
Production Operations & Reliability
- Own platform reliability for AI services serving multiple business units.
- Implement observability, monitoring, and alerting for ML pipelines and inference services.
- Drive cost optimization across data platform workloads, cloud compute, and storage infrastructure.
- Proficient in using Azure Machine Learning Studio to manage the full lifecycle of models, including registration, versioning, and monitoring.
YOU MUST HAVE
- 8 plus years of experience in software engineering, data engineering, or ML platform engineering.
- Strong proficiency in Python and at least one systems language (Python, Go, Rust, C++).
- Deep hands-on experience with cloud-native data platforms (Databricks, BigQuery, Azure Data Lake, Kubernetes).
- Production experience building and deploying ML/AI pipelines including model serving, feature engineering, and experiment tracking.
- Experience with LLM application frameworks such as LangChain, LangGraph, and Langsmith or equivalent agentic AI orchestration tools.
- Experience with edge AI deployment on NVIDIA Jetson or similar embedded GPU platforms.
- Experience with knowledge graphs, ontology engineering, or semantic web technologies.
WE VALUE
- Bachelor's / Advanced degree in Computer Science, Artificial Intelligence, or related field.
- Background in building management systems, HVAC, energy management, or industrial IoT domains.
- Strong leadership and management skills.
- Experience working in an agile development environment.
- Proven ability to drive successful cloud development projects and initiatives.
- Ability to work in a fast-paced and dynamic environment.
- Attention to detail and excellent problem-solving capability.
ABOUT HONEYWELL
Honeywell International Inc. (NYSE: HON) invents and commercializes technologies that address some of the world’s most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe. Learn more here: https://www.honeywell.com/us/en
BENEFITS OF WORKING FOR HONEYWELL
In addition to a performance-driven salary, cutting-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information: https://benefits.honeywell.com/
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Posting date: 5/21/2026