Hybrid AI/ML Software Engineer II: LLMs & GenAI

Honeywell International, Inc.; Phoenix (AZ); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Honeywell International, Inc. seeks an Engineer II to develop, test, and integrate AI/ML capabilities into software products. You will work with experienced AI and software engineers to build reliable, scalable AI-powered solutions in Phoenix, AZ on a hybrid schedule.

Initial 90 days require onsite 100% M-F. You will collaborate across product, data, software, and platform teams, contribute to architecture reviews, and help deploy AI models while maintaining quality and security standards.

Qualifications

• 2+ years of hands-on AI/ML software engineering experience, including developing and deploying AI/ML solutions in production environments.

Responsibilities

• Build apps using LLMs and Generative AI.
• Develop prompt workflows, embeddings, and semantic search.
• Create Python-based AI/ML applications and APIs.
• Integrate AI models with existing software.
• Assist with model evaluation, testing, and optimization.
• Deploy, monitor, and maintain AI/ML solutions.
• Collaborate with cross-functional teams to deliver AI solutions.
• Participate in architecture, design, and code reviews.
• Troubleshoot AI/ML and software issues; perform root-cause analysis.
• Ensure quality, reliability, security, and maintainability of AI solutions.

Skills

AI/ML engineering

Python

Prompt engineering

LLMs

Generative AI

Distributed systems

Software testing

Education

Bachelor’s or Master’s in CS or related field

Tools

Docker

Kubernetes

CI/CD

Azure Cloud

Gemini Cloud

Job description

Honeywell International, Inc. seeks an Engineer II to develop, test, and integrate AI/ML capabilities into software products. You will work with experienced AI and software engineers to build reliable, scalable AI-powered solutions in Phoenix, AZ on a hybrid schedule.

Initial 90 days require onsite 100% M-F. You will collaborate across product, data, software, and platform teams, contribute to architecture reviews, and help deploy AI models while maintaining quality and security standards.