Sr AI Manager

Sr AI Manager (B4)

Position Description:

Honeywell's Value Engineering (VE) and Component Engineering (CE) Center of Excellence (COE) is a dynamic collective of professionals dedicated to refining product development through innovative engineering and strategic component selection.

You will be part of Honeywell's VE/CE CoE Advanced Tech team driving Tech Charter & Strategy with focus on how AI/ML can enable us meet VE/CE revenue targets.

You will be responsible to drive end-to-end delivery of AI programmes by partnering with AI technical leadership and SMEs, translating strategy into structured execution plans and measurable business outcomes. Drive execution rigor across AI initiatives through strong programme governance, stakeholder alignment, and disciplined delivery practices to ensure quality and predictability. Drive adoption, value realisation, and compliance by enabling robust evaluation, testing, documentation, and governance frameworks across all AI tracks. Drive organisational growth and capability by building a high-performing team, scaling talent, managing resource and budget planning, and evolving tools and systems to support sustainable AI delivery.

Key Responsibilities:

• Lead the end-to-end delivery of AI programs, partnering with AI technical leadership and SMEs to translate strategy into executable plans and measurable business outcomes.

• Drive execution rigor across AI initiatives using strong program management practices (planning, governance, risk mitigation, stakeholder communication) to ensure predictable and high-quality delivery.

• Collaborate with vendors and cross-functional teams (IT, business, and functional groups) to enable seamless delivery, integration, and adoption of AI solutions across the organization.

• Own requirements evaluation, testing, adoption, and value realization for all AI tracks, ensuring solutions are effectively operationalized and deliver tangible impact.

• Establish and enforce robust documentation and governance standards, including model lineage, evaluation frameworks, compliance requirements, and audit-ready artefacts.