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Senior IT Manager, AI Transformation

Senior IT Manager, AI Transformation

HoneywellPhoenix, AZ, US
Hace 6 días
Tipo de contrato
  • A tiempo completo
Descripción del trabajo

Senior Manager Of It And Ai Transformation

As a senior manager of IT and AI transformation at Honeywell Aerospace Technologies, you will be at the forefront of AI-enabled innovation within our S / 4HANA transformation organization. Leading a diverse team of AI specialists, data scientists, solution architects, DevOps professionals, and project managers, this role provides a unique opportunity to shape our AI strategy for ERP transformation and drive intelligent automation solutions that enhance operational capabilities, accelerate delivery, and improve business outcomes across our global S / 4HANA deployment.

You will report directly to our director of S4 E2E architecture, and you'll work out of one of our Phoenix, AZ or Charlotte, NC locations on a hybrid work schedule.

In this role, you will impact the organization by spearheading AI and intelligent automation initiatives that drive S / 4HANA transformation efficiency, enhance data-driven decision-making, accelerate testing and quality assurance, optimize change management, and foster a culture of innovation across the enterprise as part of our S / 4HANA journey.

Responsibilities

Key responsibilities

  • Lead and mentor a high-performing team of AI specialists, data scientists, solution architects, DevOps engineers, and project managers focused on AI and intelligent automation initiatives within S / 4HANA transformation.
  • Define and execute comprehensive AI strategy aligned with S / 4HANA transformation objectives, identifying opportunities to leverage AI / ML, generative AI, and intelligent automation across the transformation lifecycle.
  • Drive AI-enabled transformation capabilities including intelligent test automation, AI-assisted data migration and quality validation, predictive analytics for program risk management, and generative AI for documentation and knowledge management.
  • Collaborate with cross-functional teams including functional leads, technical architects, testing CoE, data engineering, and business process owners to integrate AI solutions that enhance transformation delivery.
  • Oversee the planning, execution, and delivery of AI projects supporting S / 4HANA transformation, ensuring they meet quality, budget, and timeline expectations while delivering measurable business value.
  • Champion SAP AI capabilities including SAP AI Core, SAP Joule (generative AI copilot), SAP Build Process Automation, and SAP Analytics Cloud with embedded AI / ML models.
  • Establish AI governance frameworks for responsible AI adoption including model validation, bias detection, explainability standards, and compliance with data privacy regulations.
  • Lead the evaluation and implementation of AI-powered tools for transformation acceleration including intelligent testing platforms, automated code analysis, AI-assisted cutover planning, and predictive hypercare analytics.
  • Drive innovation in data-driven insights by implementing AI / ML models that predict transformation risks, optimize resource allocation, forecast deployment readiness, and identify process improvement opportunities.
  • Partner with SAP and technology vendors to pilot emerging AI capabilities, evaluate new tools, and establish best practices for AI integration within S / 4HANA ecosystems.
  • Foster a culture of experimentation and continuous learning, encouraging the team to explore innovative AI use cases that can accelerate transformation outcomes and enhance user adoption.
  • Ensure integration of AI solutions with S / 4HANA architecture including SAP BTP AI services, integration with analytics platforms, and secure data pipelines for model training and inference.
  • Monitor AI solution performance and ROI, establishing metrics and dashboards that demonstrate value delivery, efficiency gains, and quality improvements from AI initiatives.
  • Champion the adoption of best practices in MLOps, AI ethics, and responsible AI development that enhance AI capabilities while maintaining security, privacy, and regulatory compliance.

Benefits of working for Honeywell

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized medical, dental, vision, and life insurance; short-term and long-term disability; 401(k) match, flexible spending accounts, health savings accounts, EAP, and educational assistance; parental leave, paid time off (for vacation, personal business, sick time, and parental leave), and 12 paid holidays.

Qualifications

You must have

  • 6+ years of experience in AI, machine learning, data science, or related technology management roles, including a minimum of 3 years in a leadership position.
  • Strong expertise in AI technologies, machine learning algorithms, natural language processing (NLP), generative AI (Large Language Models), and data analytics.
  • Proven experience applying AI / ML to enterprise transformation programs, ideally within ERP, SAP, or S / 4HANA contexts.
  • Deep understanding of AI / ML platforms and tools including TensorFlow, PyTorch, scikit-learn, and cloud-based AI services (AWS SageMaker, Azure AI, Google Vertex AI).
  • Experience with SAP AI capabilities including SAP AI Core, SAP Business Technology Platform AI services, or SAP Analytics Cloud with predictive analytics.
  • Proven ability to lead cross-functional teams, manage complex AI projects, and translate business problems into AI / ML solutions.
  • Experience with cloud platforms (AWS, Azure, GCP) and AI / ML development, deployment, and operationalization (MLOps) practices.
  • Strong knowledge of data engineering, data pipelines, and integration patterns required to support AI / ML model development and deployment.
  • Excellent problem-solving skills and the ability to communicate complex technical concepts about AI / ML to non-technical stakeholders and executive leadership.
  • Ability to work in a fast-paced, dynamic transformation environment and adapt to changing priorities while maintaining focus on value delivery.
  • We value

  • Bachelor's degree in computer science, artificial intelligence, data science, machine learning, or a related field; master's degree or PhD preferred.
  • 8+ years of experience in AI / ML with specific focus on enterprise transformation or ERP implementation contexts.
  • Experience driving AI transformation initiatives within S / 4HANA programs or large-scale SAP implementations.
  • Deep familiarity with SAP Joule (generative AI copilot), SAP AI Business Services, SAP Build Process Automation, and SAP BTP AI capabilities.
  • Expertise in generative AI, Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG) architectures.
  • Experience with AI-powered testing tools, intelligent automation platforms (UiPath, Automation Anywhere, Blue Prism), and AI-assisted quality assurance.
  • Knowledge of SAP data architecture, SAP HANA database, and integration of AI / ML models with S / 4HANA business processes.
  • Background in Aerospace & Defense, Manufacturing, or regulated industries with understanding of compliance requirements for AI solutions.
  • Certifications in AI / ML (AWS Certified Machine Learning, Google Professional ML Engineer, Azure AI Engineer) or SAP AI certifications.
  • Strong leadership and mentoring skills with track record of building and developing high-performing AI and data science teams.
  • Exceptional communication and interpersonal skills, with the ability to inspire and influence at all organizational levels, from technical teams to executive stakeholders.
  • Familiarity with Agile methodologies, DevOps practices, and modern project management frameworks for AI / ML initiatives.
  • Experience with responsible AI frameworks, AI ethics, model governance, and regulatory compliance (EU AI Act, industry-specific regulations).
  • Proven ability to balance innovation with pragmatic delivery, demonstrating measurable business value from AI investments.
  • Track record of successful partnerships with technology vendors, research institutions, or AI product companies to pilot and scale innovative solutions.
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