Sr. AI Manager

Job Description

As a Honeywell Forge and AI team senior manager here at Honeywell, you will be responsible for designing and evolving our AI technology landscape for Honeywell Forge products. This hands‑on leadership role will shape our AI ML roadmap, ensure technical execution and deliverables, oversee a team through technical leadership and talent management, and champion the value of AI both internally and externally.

The ideal candidate will combine deep technical expertise with exceptional communication and mentorship skills.

Collaborating closely with business leaders and technology teams, you'll lead our technical execution towards business goals following industry best practices. Your insights and expertise will be pivotal in identifying opportunities, addressing challenges, and ensuring the scalability, security, and compliance of our AI solutions.

You will report directly to the Director of Artificial Intelligence, and you'll work out of our Atlanta, Georgia location on a hybrid work schedule. Your contributions will be instrumental in driving innovation, addressing complex challenges of our industrial businesses, driving innovation through partnerships, and maintaining the scalability, security, and compliance of our AI technology landscape. Your role will contribute to our organization's ability to adapt, thrive, and lead in an ever‑evolving industry.

Join us, and together, we will set new standards for AI excellence at one of the globe's premier industrial technology companies.

Key Responsibilities

AI/ML Technical Execution

• Work alongside program managers and technical product owners to translate business requirements into technical plans.
• Work with technical teams to design, develop, implement and maintain AI/ML solutions.
• Hands‑on development with the team and hands‑on work with architects to design our solution and optimize implementation strategies.
• Set and enforce best practices in experimental design, model development, documentation, and reproducibility.

MLOps Best Practices

• Follow AI/ML, MLOps and LLMOps best practices.
• Collaborate with data engineering, ML engineering, and IT teams to move models from prototype to production in a reliable, maintainable way.
• Define and oversee model monitoring, performance tracking, and retraining strategies.
• Ensure solutions meet requirements for security, compliance, and data governance.

Technical Leadership & Mentorship in AI

• Provide technical guidance and oversight to AI engineers, data scientists, and product teams for Honeywell products.
• Serve as people leader managing a team of data scientists and AI engineers.
• Establish and refine standards, tools, and frameworks for data science work (coding standards, model evaluation, documentation, knowledge sharing).
• Foster a culture of curiosity, experimentation, and continuous improvement within the team.

Evangelism & Communication

• Serve as a visible champion for AI/ML initiatives within the organization and with external stakeholders.
• Communicate the value and impact of AI/ML projects to non‑technical audiences, including senior executives, customers, and partners.
• Represent the company at conferences, industry panels, and client briefings as a thought leader in AI/ML.

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as a U.S. citizen, a U.S. permanent resident, or someone with protected status in the U.S. under asylum or refugee status or having the ability to obtain an export authorization.

Must Have

• Minimum 7 years of experience in machine learning, AI engineering, data science development roles, experience in defining and developing AI/ML solutions and at least 3 years in a technical leadership role.
• Minimum 3 years of technical development experience, holding data science, machine learning engineer related titles and showing clear career progression in this domain.
• Minimum 5 years hands‑on experience coding with Python, Spark, SQL, leveraging common libraries such as Tensor Flow, Keras, to solve conventional machine learning problems.
• Minimum 2 years of hands‑on experience building LLM‑related solutions (RAG,…