AI Platform Owner

The Hershey Company•Dallas, TX

4d•$136,160 - $170,150•Onsite

About The Position

The AI Platform Owner is responsible for defining, governing, and scaling Hershey's enterprise AI platform ecosystem. This role owns the standards, reusable components, and operating models that enable rapid, repeatable deployment of AI solutions across the organization. Rather than supporting one-off AI implementations, the position establishes and maintains a scalable "AI Factory" capability that allows business functions to develop and deploy AI solutions through standardized platforms, templates, and governance frameworks. This role serves as the enterprise authority on AI platform strategy and tool selection, ensuring the appropriate use of technologies including Microsoft Copilot, Copilot Studio, Azure AI, Databricks/Genie, Claude, Gemini, and related AI platforms. The position is responsible for establishing decision frameworks that guide when and how specific AI technologies should be used, preventing fragmented or preference-based adoption across the enterprise. The role leads moderately complex technical programs and platform initiatives spanning multiple business and technology domains, influencing long-term architecture decisions while ensuring alignment with enterprise standards, security requirements, governance controls, and scalability objectives. The AI Platform Owner partners closely with Function AI Leads, Data & Platform teams, Product Management, Governance, and Security teams to deliver reliable, governed, and reusable AI capabilities at enterprise scale.

Requirements

7+ years of experience in technology, cloud platforms, AI/ML platforms, or related technical disciplines.
Experience owning, managing, or leading enterprise-scale technology, data, cloud, or AI platforms.
Demonstrated experience in frameworks, templates, or delivery capabilities that enable scalable and repeatable solution deployment.
Experience establishing technology standards, governance frameworks, and platform operating models across multiple teams and business functions.
Experience leading complex, cross-functional initiatives involving technical and business stakeholders.
Proven ability to influence technical strategy and architecture decisions across multiple business domains.
Strong communication skills with the ability to explain complex technical concepts and platform trade-offs to both technical and non-technical stakeholders.
Bachelor's Degree in Computer Science, Information Systems, Systems Engineering, Technology, or a related technical field.

Nice To Haves

Experience building and scaling enterprise AI, automation, or agent-based platforms.
Knowledge of AI governance, responsible AI practices, platform security controls, and compliance requirements.
Strong understanding of cloud architecture, data platforms, integrations, APIs, and enterprise technology ecosystems.
Experience developing AI platform decision frameworks and tool selection standards.
Experience working within highly matrixed organizations and driving adoption of enterprise technology standards.

Responsibilities

Own the enterprise AI platform ecosystem, including platform selection, standards, configurations, governance requirements, and roadmap planning. Define and maintain enterprise AI platform strategy while evaluating emerging technologies and capabilities. Partner with technical and business stakeholders on build-versus-buy decisions and ensure alignment with enterprise architecture standards, security requirements, and long-term business objectives.
Lead the development and continuous improvement of the enterprise AI Factory capability by creating reusable templates, patterns, accelerators, tooling, and deployment frameworks that enable rapid and repeatable AI solution delivery. Ensure new AI agents and solutions can be deployed through standardized approaches rather than bespoke development efforts. Drive consistency, scalability, and maintainability across multiple teams and business functions.
Serve as the enterprise subject matter expert for AI platform selection and usage patterns. Establish decision frameworks and standards that guide when technologies such as Copilot, Copilot Studio, Azure AI, Databricks/Genie, Claude, Gemini, and other AI tools should be utilized. Develop and communicate enterprise guidelines that clarify when AI solutions are appropriate, when advanced AI platforms are justified, and when traditional solutions may better meet business requirements.
Guide cross-functional teams including Function AI Leads, Product Management, Engineering, Data & Platform teams, Operations, Governance, and Security stakeholders to align on platform capabilities, adoption strategies, and technical decisions. Coordinate dependencies, manage risks, and ensure technical standards are consistently applied across AI initiatives. Break down complex platform challenges into executable workstreams and drive delivery against established objectives.
Establish and oversee platform-level controls, monitoring, telemetry, usage analytics, and governance mechanisms to ensure secure, compliant, and effective AI adoption. Partner with Governance and Security teams to implement enterprise controls and reporting capabilities. Ensure platform metrics, usage visibility, and operational insights support enterprise governance requirements and continuous improvement efforts.
Collaborate with Enterprise Architecture and Data & Platform teams to evaluate platform capabilities, solution patterns, integrations, and architectural approaches. Provide technical leadership regarding scalability, security, performance, supportability, and maintainability considerations. Balance short-term delivery priorities with long-term architectural goals and platform sustainability.
Partner with Product Managers and delivery teams to ensure AI platforms are ready to support roadmap priorities and business initiatives. Define platform readiness criteria, support implementation planning, validate non-functional requirements, and oversee the transition of AI capabilities into operational environments. Ensure platforms deliver measurable business value and maintain operational reliability.