Sr Mgr, Software Engineering
About The Position
At Disney Experiences Technology, our team creates world-class immersive and digital experiences for the Company’s vacation brands, Disney’s Parks and Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club. The Disney Experiences Technology team is responsible for the end-to-end digital and physical Guest experience for all technology & digital-led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation, and Merchandise lines of business as well as other initiatives including the MyDisneyExperience app and Hey, Disney! Our team delivers large-scale, data-driven initiatives that enable business insight, operational efficiency, and enterprise-wide value across Disney Experiences. The DX Transformation Delivery Management Organization (DMO) partners closely with Business Functional Teams, Product, Engineering, Architecture, and Technology leaders to execute complex, initiatives that accelerate value by enabling data analytics and AI-ready capabilities at scale. The Senior Manager, AI Delivery Execution sits at the leading edge of the DX Technology Transformation team, responsible for embedding AI and automation into every transformation initiative to drive scaled, compounding value over time. They will identify high-impact opportunities, building business cases, designing solutions, and driving execution through to production fully integrated into the platforms, processes, and workflows that power the DX segment. The role requires deep technical expertise in AI and automation, a strong focus on measurable outcomes, and the leadership presence to influence senior stakeholders, drive adoption, and build a high-performing team that consistently delivers at the edge of what’s possible.
Requirements
- 10+ years of experience in AI, machine learning, data engineering, or automation, with at least 3 years in a leadership role managing technical teams in an enterprise environment.
- Proven delivery record taking AI and automation capabilities from concept through production in complex, matrixed organizations — with demonstrated, measurable business outcomes.
- Deep technical fluency in applied AI/ML — including large language models, generative AI, agentic workflows, machine learning pipelines, and enterprise automation patterns (RPA, workflow orchestration, intelligent process automation).
- Strong business value orientation: the ability to translate technical AI capability into a clear business case, quantify potential value, and track realized outcomes against that case post-deployment.
- Experience designing and deploying reusable AI/automation frameworks or accelerators that scale across multiple programs, functions, or business units — not just one-off point solutions.
- Demonstrated ability to integrate AI and automation capabilities into enterprise data platforms, operational systems, and business workflows — not just build them in isolation.
- Strong cross-functional leadership skills, including the ability to influence senior stakeholders without authority, navigate organizational complexity, and drive alignment across diverse teams.
- Experience managing and developing technical teams, including performance management, career development, and building a culture of delivery excellence and continuous learning.
- Executive-level communication skills: comfortable translating complex AI concepts into business language for VP and SVP audiences, and building the credibility to be a trusted advisor on AI strategy.
- Experience working in a segment-wide or enterprise-wide context, where solutions must scale across multiple business units with differing operational models and technology landscapes.
- AI & Machine Learning: Applied experience with large language models (LLMs), generative AI, retrieval-augmented generation (RAG), and agentic AI frameworks in enterprise production environments.
- Proficiency with ML lifecycle management — including model training, evaluation, deployment, monitoring, and responsible AI governance (bias, fairness, explainability).
- Familiarity with AI platforms and tooling such as Azure OpenAI, AWS SageMaker, Databricks, or equivalent enterprise AI infrastructure.
- Automation & Integration: Hands-on experience with enterprise automation patterns including RPA, workflow orchestration (e.g., Apache Airflow, Azure Logic Apps), and intelligent process automation.
- Experience integrating AI and automation capabilities with enterprise data platforms, ERP/EPM systems, and operational workflows.
- Familiarity with data engineering fundamentals — pipelines, transformation, data quality, and the data readiness requirements that underpin AI effectiveness.
- Platforms & Tooling: Experience with cloud-native data and AI platforms (Azure, AWS, GCP) and modern data platform architectures (lakehouses, data meshes, semantic layers).
- Familiarity with BI and analytics tooling (Tableau, Power BI) and how AI-generated insights are surfaced and consumed by business users.
- Proficiency with delivery and collaboration tools including Jira, Confluence, and Smartsheet.
Nice To Haves
- Experience in a theme park, hospitality, retail, or large-scale consumer operations environment where AI and automation were applied to operational efficiency or financial insight use cases.
- Experience building AI capabilities on top of a centralized data platform or data lakehouse architecture.
- Familiarity with enterprise performance management (EPM) systems and the data and AI use cases they enable.
- Experience delivering AI programs with international scope, including awareness of regional data privacy regulations (GDPR, PDPA, PIPL) and cross-border data governance.
- Prior experience operating as the “AI center of excellence” function within a large organization, establishing standards, governance, and a use-case pipeline.
Responsibilities
- Define and own the AI and automation strategy, prioritizing and delivering use cases aligned to business goals while leading end‑to‑end execution—from definition and design through engineering, testing, integration, and production deployment within transformation programs.
- Design reusable AI and automation accelerators — patterns, frameworks, and components — that can be deployed across multiple DX businesses, functions, and programs, compounding value at the segment level.
- Partner with technology teams to align on AI capability roadmaps, data readiness requirements, and the governance model for AI tools built on the centralized data platform.
- Establish delivery standards for AI and automation engineering — including solution design, model governance, testing rigor, deployment reliability, and production monitoring — ensuring quality and sustainability at scale.
- Accountabile for engineering quality, technical standards, and scalable solution delivery
- Lead, manage, and develop a high-performing team, providing clarity of direction, technical mentorship, and accountability for delivery excellence.
- Serve as a trusted strategic partner to senior business leaders across Finance, HR, and other functional areas — helping them understand what AI can and cannot do, building realistic expectations, and co-designing solutions that drive adoption and lasting value.
- Communicate AI and automation strategy, progress, and outcomes to executive audiences — including Directors, VPs, and SVPs — through clear, business-grounded narratives that connect technical work to segment-level value.
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
