Sr Advanced AI Platform Engineer

Honeywell; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Performance-driven salary

Employer-subsidized Medical, Dental, Vision, and Life Insurance

401(k) match

Flexible Spending Accounts, Health Savings Accounts

Parental Leave

12 Paid Holidays

Job summary

Honeywell is looking for a Full Stack AI Platform Engineer located in Atlanta, GA. This key role involves designing and building a robust AI/ML platform that supports intelligent automation across various sectors.

The ideal candidate will have over 8 years of experience in software and data engineering, proficiency in Python, and familiarity with cloud-native platforms. Benefits include a performance-driven salary and employer-subsidized insurance.

Qualifications

• 8 plus years of experience in software engineering, data engineering, or ML platform engineering.
• Deep hands-on experience with cloud-native data platforms.
• Production experience with ML/AI pipelines including model serving and experiment tracking.

Responsibilities

• Develop high-performance, production-ready Python APIs using FastAPI.
• Design and maintain AI/ML platform services on multi-cloud infrastructure.
• Implement ML orchestration workflows and automate data processing pipelines.

Skills

Python

Cloud-native platforms

Data engineering

Machine Learning (ML)

CI/CD processes

Edge AI technologies

Observability and monitoring

Education

Bachelor's / Advanced degree in Computer Science, Artificial Intelligence, or related field

Tools

Azure ML Studio

Databricks

BigQuery

Kubernetes

NVIDIA Jetson

Job description

Full Stack AI Platform Engineer

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.

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.

Key Responsibilities

• Note: For the first 90 days, new hires must be prepared to work onsite 100% M-F.
• 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

• Integrate and run pre-built AI models on local hardware using standard industry runtimes.
• Build the software logic required to process data inputs and handle model outputs efficiently.
• Develop Python-based services and automate their deployment to devices via standardized pipelines.
• Monitor and optimize software to run reliably within strict memory and hardware limitations.
• Deploy containerized models from Azure to edge devices using Azure IoT Edge or managed online endpoints.

Data & Knowledge Engineering

• Build pipelines to structure, clean, and store data for model training or real-time retrieval (RAG) on edge devices.
• 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.

Qualifications

• 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.

Preferred Qualifications

• 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.

Benefits

• Performance-driven salary and cutting-edge work.
• 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.
• 12 Paid Holidays.