Lead Software AI Engineer

Honeywell•Phoenix, AZ

3d•Hybrid

About The Position

As a Lead Software AI Engineer at Honeywell, you will lead project teams of software engineers in designing, developing, and delivering software solutions. You will drive technical excellence and project success while contributing to the growth of the software engineering team. You will lead the strategic vision and roadmap and drive performance, reliability, and quality across software products to support scalable business growth. The role is based in Phoenix, Arizona, with a hybrid work schedule. For the first 90 days, new hires must be prepared to work onsite Monday through Friday. You will report directly to the Director of Engineering. You will lead AI-driven product innovation, architecture governance, cross-functional collaboration, lifecycle management, and team development. The work includes identifying industrial AI/ML opportunities, modernizing products, and ensuring solutions meet standards for cybersecurity, scalability, reliability, and maintainability.

Requirements

Bachelor’s degree from an accredited institution in a technical discipline such as science, technology, engineering, or mathematics.
6+ years of production AI/ML experience designing, deploying, and operating production-grade systems, with ownership of model lifecycle, reliability, and performance in real-world environments.
6+ years of mastery of machine learning, deep learning, LLMs, generative AI, and RAG, with the ability to evaluate, select, and operationalize state-of-the-art techniques for industrial use cases.
6+ years of strong Python proficiency and hands-on experience building distributed systems, APIs, microservices, and scalable data/ML pipelines.
6+ years of cloud-native deployment experience using Azure or AWS, including Docker/Kubernetes and CI/CD workflows tailored for ML/LLM systems.
Ability to influence architecture decisions, define reference patterns, and ensure AI systems meet standards for scalability, cybersecurity, and long-term maintainability.
6+ years of cross-functional leadership experience collaborating with engineering, data science, product, and field teams to translate business needs into actionable AI/ML solutions.
Must be a U.S. Person (U.S. citizen, U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status) or have the ability to obtain export authorization.

Nice To Haves

Master’s degree (PhD preferred) in Computer Science, AI/ML, Data Science, Electrical Engineering, or a related field.
Experience with industrial automation, control systems, or OT networking.
Knowledge of Honeywell Control Transformers, Network/FTE architectures, or similar industrial product lines.
Hands-on work with multi-agent systems, autonomous agents, or edge AI, including orchestrating distributed intelligence across constrained or mission-critical environments.
Experience with AI safety, governance, and explainability, ensuring models meet enterprise standards for transparency, robustness, and responsible deployment.
Publications, patents, or open-source contributions in AI/ML demonstrating thought leadership, innovation, and engagement with the technical community.

Responsibilities

Identify and deliver AI/ML opportunities, including predictive maintenance, diagnostics, network optimization, forecasting, and LLM-based assistance.
Lead engineering teams building scalable AI/ML systems for industrial environments.
Develop and protect intellectual property for AI models, control algorithms, and network optimization.
Participate in Architecture Council meetings and help align product and architecture decisions.
Provide input on reference architecture and technology choices.
Ensure AI features meet cybersecurity, scalability, and architectural standards.
Collaborate with engineering, data science, architecture, commercial, and field teams.
Communicate product decisions and priorities across the LSS/PA leadership team and other Honeywell groups.
Drive innovative, high-quality, and cost-effective technical solutions.
Lead modernization and the Control Transformer and Network/FTE product roadmaps.
Improve reliability, reduce downtime, and optimize network performance.
Ensure long-term maintainability, cybersecurity, and scalability.
Mentor teams and foster a culture of ownership and innovation.
Support talent development and team engagement.
Champion diversity, inclusion, and high performance.