Senior AI Engineering Leader | Production ML & MLOps

Honeywell International Inc.; Dublin; Hybrid; EUR 180,000 - 240,000; Full time

Benefits offered by this job

Brand with innovation focus

Internal promotion culture

Inclusive, diverse environment

Job summary

Honeywell Ireland seeks a Senior AI Engineering Manager to lead a global AI engineering capability, directing roadmaps, portfolio direction, talent strategy, customer-facing technical leadership, and scalable AI delivery across production environments.

You will combine people leadership with hands-on technical engagement, shaping the AI roadmap, guiding architecture and implementation, and ensuring reliability, security, responsible AI, and cost controls.

Qualifications

• Bachelor's degree required in CS/Software Engineering/AI or related field.
• 10+ years in software/ML engineering or AI product development.
• 4+ years leading technical teams with direct people-management.
• 5+ years hands-on software development with Python and production engineering (APIs, CI/CD, testing).
• Proven delivery of enterprise-grade AI/ML systems from experimentation to production.

Responsibilities

• Translate customer and product requirements into AI roadmaps, architectures, milestones, and delivery plans.
• Lead end‑to‑end engineering from rapid experimentation to production release and operation.
• Oversee architecture reviews, design decisions, and code reviews; prototype when needed.
• Drive full‑stack AI solutions including data pipelines, model integration, APIs, microservices, and deployment across cloud/on-prem/edge.
• Ensure security, reliability, cost awareness, and governance across AI platforms.

Skills

Leadership

AI engineering

Python

Cloud

MLOps

Communication

Strategic planning

Education

Bachelor's degree in CS/Software Engineering/AI

Master's degree in CS/Software Engineering/AI

Tools

Docker

Kubernetes

PyTorch

TensorFlow

MLflow

Job description

Honeywell Ireland seeks a Senior AI Engineering Manager to lead a global AI engineering capability, directing roadmaps, portfolio direction, talent strategy, customer-facing technical leadership, and scalable AI delivery across production environments.

You will combine people leadership with hands-on technical engagement, shaping the AI roadmap, guiding architecture and implementation, and ensuring reliability, security, responsible AI, and cost controls.