Engineer, AI Strategy and Solutions

At Universal Creative we design develop and deliver the most compelling entertainment experiences imaginable to drive growth for Universal Destinations & Experiences worldwide. Our innovative attractions immersive theme parks and world-class resorts fuse art and technology to create new standards in the themed entertainment industry.

Our Team Members are the driving force behind Universal Creative. With their diverse skills and forward-thinking ideas our team pushes us beyond the boundaries of whats possible to achieve the extraordinary. Together were creating a Universe of fun always ensuring the next thing we do is better than the last thing we did.

JOB SUMMARY:

The Engineer AI Strategy & Solutions is responsible for designing and building AI-enabled and conventional software systems that integrate with enterprise data platforms services and event-driven architectures to deliver measurable business value. This role translates complex business and technical requirements into scalable production-ready solutionsincluding APIs data pipelines and model serving infrastructure (batch and real-time)using established platform patterns.

Key responsibilities include implementing AI capabilities such as inference retrieval-augmented generation (RAG) and evaluation workflows while ensuring compliance with Responsible AI principles security standards and privacy controls throughout the development lifecycle.

The engineer owns the quality of delivered solutions including comprehensive testing (unit integration end-to-end) performance profiling and observability through logs metrics and traces. Participation in on-call rotations and incident response is expected.

This role collaborates closely with cross-functional teams including Product Data Science Security and Infrastructure. It involves contributing to design reviews authoring clear technical documentation and runbooks and advancing shared libraries SDKs and CI/CD/MLOps practices. #LI-DNI

MAJOR RESPONSIBILITIES:

• AI & Cloud Software Engineering:

  • Provides technical support to project teams on the design development and delivery of AI-enabled and conventional software translating requirements into designs and working code while aligning to platform standards and patterns.
  • Maintains knowledge of enterprise software/AI standards (architecture security/privacy data contracts responsible AI) and industry best practices.
  • Provides support to project teams to design build and deploy AI-enabled and conventional systems that meet safety reliability performance and compliance requirements.
  • Assists cross-functional teams and studio leadership to deliver global multi-platform software and AI solutions across web mobile console and edge environments.
  • Supports complex delivery across diverse platforms and geographies aligning technical execution with business goals.

• Cross-functional quality assurance:

  • Review internal and vendor deliverablesAPI/architecture docs data schemas model cards security/privacy checklists test plans (unit/integration/load/perf) and test resultssubmit redlines/issues and track to resolution.
  • Supports lifecycle technical reviews and readiness gatesrequirements and architecture reviews threat modeling model card/data lineage checks test plan definition (offline evals A/B load/perf) deployment/go-live approvals.
  • Ensures alignment with standards and best practices.
    
    
• Applied AI Engineering & Operations:
  
  
  • Contribute directly to engineering work: build/integrate services & APIs ETL/streaming data pipelines model training/inference code and RAG/retrieval flows; author automated tests; participate in operational support/on-call.
  • Supports continuous improvement of engineering processes templates and tooling (coding standards shared SDKs/libraries CI/CD & MLOps pipelines evaluation/observability incident response).
  • Supports product/production teams with feature breakdown estimation and technical risk management.
  • Proactively identify dependencies and risks facilitate resolution and maintain momentum across complex initiatives. By bridging product vision with engineering execution this role drives operational clarity and accelerates value realization.
• AI Platform Engineering & Developer Enablement:
  
  
  • Create and maintain engineering artifactsdesign docs ADRs runbooks deployment playbooks IaC/config.
  • Contribute to shared SDKs/templates and CI/CD/MLOps pipelines; ensure portability maintainability reliability observability operability and supportability.
  • Collaborate with engineers across Associate/Engineer/Senior bands; participate in targeted internal workshops (AI solution patterns secure coding platform usage Responsible AI) elevating overall engineering quality and velocity.
  • Ensures that all systems and models are built with integrity accountability and resilience from the ground up.
  • Supports and models best in class culture which promotes innovation collaboration and problem-solving. Inspires and motivates teams by leading with optimism and a solution-oriented approach drives for results.
    
    
• Understand and actively participate in Environmental Health & Safety responsibilities by following established UO policy procedures training and team member involvement activities.
• Performs other duties as assigned.

ADDITIONAL INFORMATION:

• Required: Proficient in Python plus one of C#/Java/Go/TypeScript/C; experienced with REST/gRPC APIs microservices event-driven architecture and integration with internal/external services. Works with SQL/NoSQL and data pipelines (ETL/ELT batch/streaming); familiar with Kafka/Kinesis/PubSub or similar. Deploys on AWS/Azure/GCP using containers/Kubernetes IaC and CI/CD; applies MLOps basics (model registry/versioning feature stores drift detection). Applies security-by-design (authN/Z secrets PII handling) and Responsible AI practices (model cards eval gates); writes maintainable docs and performs effective code reviews.
• Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
• Consistent attendance is a job requirement.

EDUCATION:

• Bachelors degree in a relevant technical field e.g. Computer Science Software Engineering Computer Engineering Data Science/Analytics Electrical Engineering (software focus) or Systems Engineering or equivalent demonstrated skill and experience (e.g. production-software/AI systems open-source contributions published work) required; or equivalent combination of education and experience.
• Masters degree in Computer Science AI/ML Data Science Software Engineering or a closely related field preferred.
• Graduate coursework or certifications in machine learning distributed systems/cloud MLOps security/privacy or data engineering are a plus.

EXPERIENCE:

• 5 years delivering multi-platform networked software (web mobile services edge) to production.
• Hands-on AI solutioning (e.g. computer vision NLP/RAG anomaly detection personalization) with training & inference pipelines evaluation and monitoring; or equivalent combination of education and experience.

Your talent skills and experience will be rewarded with a competitive compensation package.