Principal Applied AI & Business Acceleration Manager (Remote)

TE Connectivity Ltd•Middletown, OH

40d•Remote

About The Position

The Principal, AI & Business Enablement is a hands-on leader who will embed AI and automation across Channel BU business operations to deliver measurable impact on growth, efficiency, and customer experience. This role blends product ownership and capability enablement-driving flagship AI initiatives while educating and enabling teams to integrate AI in everyday work. This role is designed to accelerate Channel's transformation into an AI-first organization - one that drives commercial impact through intelligent automation, empowered teams, and responsible innovation. The Principal, AI & Business Enablement will act as the connective tissue between business opportunities, digital capabilities, and advanced analytics solutions, ensuring every AI initiative delivers tangible value to their distributors, customers, and internal teams.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, or related field; advanced degree (MBA, MS, or equivalent) preferred.
10+ years of experience in digital product management, applied AI, or data strategy, ideally within complex, matrixed organizations.
Proven track record delivering measurable business outcomes through AI, automation, or digital transformation.
Hands-on experience with LLMs, prompt engineering, Python scripting, or workflow automation.
Strong understanding of data systems (e.g., Databricks, Snowflake, Azure Synapse, SAP, Salesforce) and governance principles.
Exceptional ability to translate complex technical concepts into business-relevant narratives and use cases.
Strong communication and influence skills; able to inspire adoption and align senior stakeholders.

Responsibilities

Lead end-to-end design and delivery of AI-powered tools and automation solutions across Marketing, Sales, Customer Care, and Digital teams.
Identify and prioritize high-value AI, advanced analytics, and data science use cases tied to Channel strategic priorities. Establish a demand management framework to identify and prioritize AI and advanced analytics initiatives.
Build ROI-based business cases and own success metrics from prototype through scale.
Translate business problems into actionable AI and automation initiatives, partnering with data, tech teams, and process owners, as needed, to implement solutions.
Evaluate emerging technologies, including agentic AI, LLMs, and cognitive automation, assessing their fit with current and future data capabilities.
Evangelize AI adoption by demonstrating practical use cases that improve day-to-day productivity and decision-making.
Develop "AI Quick Start" programs, playbooks, and hands-on learning sessions to upskill teams.
Role model the use of AI productivity tools (Microsoft Copilot, ChatGPT Enterprise, etc.) across functions.
Build and sustain an AI community of practice within the Channel to share lessons learned, tools, and best practices.
Partner closely with Data & Analytics teams to ensure priority AI use cases have the data access and quality needed for execution.
Identify critical data gaps associated with top AI initiatives and collaborate to resolve them.
Recommend lightweight data improvements that directly accelerate AI delivery - such as curated datasets, tagged attributes, or simplified integrations.
Act as the business bridge, translating AI requirements into precise data needs while ensuring alignment with existing governance and security standards.
Leverage enterprise data platforms (Salesforce, SAP, Databricks, etc.) where relevant to active AI projects, not as a standalone scope.
Establish and communicate clear principles for responsible AI use, ensuring ethical, transparent, and compliant application.
Develop KPIs and dashboards to track AI adoption, impact, and return on investment.
Measure business value delivered through AI - such as revenue growth, cost avoidance, and efficiency gains.
Stay current on emerging AI tools and technologies.
Evaluate partnerships with vendors, startups, and enterprise teams to accelerate deployment.
Encourage experimentation through safe pilot environments - enabling fast learning cycles and scaling of successful ideas.