Manager, Machine Learning Engineering

"We Power the Magic!" That’s our motto at Disney Experiences (DX) Tech & Digital. Our team creates world-class immersive digital experiences for the Company’s premier vacation brands including Disney’s Parks & Resorts worldwide, Disney Cruise Line, Aulani, a Disney Resort & Spa, and Disney Vacation Club.  

We are 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 My Disney Experience and Hey, Disney!  

This role sits on the JedAI team, the AI enablement platform that supports the entire DX organization within Technology for Disney Experiences. It works closely with partners from across the company to bring Generative AI and LLM-powered capabilities into production.  

The Manager, Software Engineering, AI/ML will report to the Senior Manager, AI/ML Engineering.  

About The Role & Team:  

• The DXT AI Technology Platform team (JedAI) is responsible for building an AI enablement platform for the DX segment, providing streamlined AI and Generative AI capabilities the segment can build solutions around and on top of. The Manager, AI/ML leads a pod of Senior and Lead full-stack AI/ML engineers responsible for designing, building, and operating GenAI/LLM-powered applications, services, and platform capabilities – spanning model integration and RAG pipelines through the APIs and front-end experiences that expose them.  

• This is a people-management and delivery-leadership role. You will set technical direction in partnership with Principal Architects, remove roadblocks, and hold the team to a high engineering bar, while working closely with product, platform, and technology leadership to translate strategy into shippable, production-grade AI systems. You will stay conversant across the full stack – GenAI/LLM services, data pipelines, APIs, and UI – without being the primary hands-on architect for any one layer.  

What You’ll Do:  

People Leadership & Talent Development  

• Hire, coach, and manage performance for a pod of Sr. and Lead AI/ML full-stack engineers, including goal-setting, career development planning, and calibration.  

• Build an inclusive, high-performing team culture that attracts and retains top AI/ML engineering talent; champion diversity of thought and background across the team.  

• Mentor engineers on technical growth, GenAI/LLM best practices, and craftsmanship, partnering with Principal/Staff engineers on structured growth plans.  

• Conduct regular 1:1s, performance reviews, and provide timely, constructive feedback; manage performance improvement plans when needed.  

Delivery & Execution  

• Own day-to-day delivery for the team’s AI/GenAI and full-stack initiatives, ensuring on-time, high-quality delivery of POCs, MVPs, and production releases.  

• Run Agile ceremonies (sprint planning, backlog refinement, estimation, retrospectives) and manage sprint capacity, staffing, and prioritization trade-offs.  

• Partner with Product Management and Principal Architects to translate roadmap and strategy into scoped, sequenced, and estimated engineering work.  

• Track and report delivery status, risks, and dependencies to the Senior Manager and cross-functional stakeholders; escalate and resolve blockers.  

Technical Guidance & Quality Standards  

• Maintain working fluency across the team’s technology stack (LLM/GenAI integration, RAG, prompt engineering, APIs, front-end frameworks, cloud infrastructure) sufficient to review designs, participate in architecture discussions, and make informed trade-off calls – without being the team’s primary hands-on implementer.  

• Uphold engineering standards for code quality, testing, security, observability, and documentation across the team’s deliverables.  

• Partner with Architecture, Security, Legal, and Responsible AI stakeholders to ensure solutions comply with ethical guidelines, data privacy requirements, and enterprise governance standards.  

• Drive adoption of new tools, frameworks, and engineering practices that improve team velocity, quality, and platform scalability.  

Cross-Functional Collaboration  

• Act as a trusted engineering partner to Product, UX, Data, Platform, and Architecture teams, ensuring alignment on scope, timelines, and technical approach.  

• Represent the team in cross-functional planning, technical reviews, and stakeholder updates; communicate technical concepts clearly to both technical and non-technical audiences.  

• Collaborate with other Engineering Managers and Architects across JedAI to share patterns, reduce duplication, and align on platform-wide standards.  

• Support recruiting, vendor/contractor management, and resource/budget planning for the team in partnership with the Senior Manager.  

Required Qualifications:  

Manager, Software Engineering – AI/ML  

• 8+ years of professional software engineering experience, including full-stack development for enterprise-scale, cloud or hybrid-cloud applications.  

• 3+ years of experience directly managing software engineers, including hiring, performance management, coaching, and career development.  

• Working knowledge of Generative AI / LLM application patterns – RAG, prompt engineering, agents, fine-tuning, and LLM Ops – sufficient to guide technical decisions and review designs with senior engineers.  

• Familiarity with core AI/ML frameworks and tooling (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) and vector/data stores (e.g., Vertex, MongoDB, CosmosDB) at a working, not necessarily hands-on-implementation, level.  

• Experience with cloud platforms (AWS, Azure, or GCP), containers (Docker, Kubernetes), and CI/CD tooling (Git, Jenkins, Artifactory or similar).  

• Working understanding of full-stack technologies – Python, Java/JavaScript, React/Node.js, REST/JSON APIs – sufficient to review code, unblock engineers, and evaluate technical trade-offs.  

• Practical experience running Agile/Scrum teams, including sprint planning, estimation, and backlog management.  

• Strong stakeholder management, negotiation, and communication skills; ability to translate complex technical concepts for executive and non-technical audiences.  

• Demonstrated track record of building inclusive, high-performing engineering teams and developing talent into more senior roles.  

• Understanding of data privacy, responsible AI, and compliance considerations relevant to enterprise Generative AI deployments.  

Preferred Qualifications:  

• Direct prior experience managing engineers who build GenAI/LLM-powered products or platforms.  

• Experience with LLM observability/evaluation tooling such as Arize, Phoenix, or similar platforms.  

• Familiarity with queuing technology (Kafka, RabbitMQ, SQS, Kinesis) and data processing tools (Spark, EMR, Glue).  

• Familiarity with Infrastructure as Code (Terraform, CloudFormation, CDK) and cloud security fundamentals (IAM, KMS, encryption).  

• Experience partnering with UI/UX teams on design systems and front-end delivery for data- or AI-heavy applications.  

• PMP, Certified Scrum Master (CSM), or equivalent project/agile delivery certification.  

• Prior experience managing engineering teams within a large, matrixed enterprise organization, ideally in media, entertainment, or consumer technology.  

Leadership & Communication:  

• People-first leadership: sets a high bar for technical quality while prioritizing team growth, well-being, and psychological safety.  

• Craft leadership: provides constructive design and code review feedback and mentors engineers in AI/ML and full-stack best practices, without needing to be the most senior hands-on engineer on the team.  

• Executive communication: clearly communicates status, risk, and trade-offs to senior leadership and cross-functional partners.  

• Change management: helps the team adapt to fast-evolving GenAI tools, frameworks, and enterprise standards while maintaining delivery stability.  

• DEI advocate: fosters a diverse and inclusive culture that encourages innovation and ensures every team member feels a sense of belonging.  

Required Education:  

• Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.  

Preferred Education:  

• Master’s degree in Computer Science, Information Systems, Software Engineering, or comparable field of study; or an MBA/technical management credential paired with a technical undergraduate degree.  

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