About the position
Corporation's corporate functions. Working in close partnership with the Data\nPlatform & Analytics Engineer, this role takes curated, AI-ready data and\ntransforms it into production-grade intelligent systems. The ideal candidate\nbrings hands-on experience in large language model orchestration, agentic\nworkflow design, and the full lifecycle of deploying and maintaining AI\nsolutions in cloud environments. This is a highly technical individual\ncontributor role at the intersection of applied AI and enterprise automation.
Responsibilities
- Design and build AI agents and multi-agent systems using Snowflake Cortex AI,\n Snowflake ML, Amazon Bedrock, LangGraph, LangChain, AutoGen, and CrewAI
- Develop agentic workflows that automate business processes across corporate\n functions
- Translate business requirements into robust, maintainable agent architectures
- Implement prompt engineering strategies, tool use, and memory patterns for\n production-grade agents
- Develop, fine-tune, and evaluate ML models using Snowflake ML, AWS SageMaker\n and Bedrock foundation models
- Design evaluation frameworks to measure model accuracy, reliability, and\n alignment with business objectives
- Select appropriate foundation models and orchestration strategies based on\n use case requirements
- Manage model versioning, experimentation tracking, and performance\n benchmarking
- Deploy AI and agent workloads to AWS infrastructure including ECS and S3
- Build CI/CD pipelines for model and agent deployment, ensuring reliable and\n repeatable release processes
- Manage containerized AI workloads and ensure high availability and\n scalability in production
- Leverage Snowflake AI tooling and Cortex capabilities to power data-driven AI\n features
- Monitor production AI systems for drift, degradation, and anomalous behavior
- Own incident response and root cause analysis for AI and agent failures in\n production
- Implement logging, observability, and alerting frameworks across all deployed\n AI solutions
- Continuously improve agent performance based on production feedback and\n stakeholder input
- Partner closely with a Data Platform & Analytics Engineer to ensure curated\n data layers meet AI consumption requirements
- Define feature requirements, data contracts, and schema standards needed for\n agent and model development
- Provide inputs on data architecture decisions that impact AI workload\n performance
- Ensure all AI solutions adhere to Carnival Corporation’s AI governance\n standards and responsible AI principles
- Apply data privacy controls and access management within AI pipelines
- Document agent architectures, model cards, and deployment runbooks to support\n audit and compliance requirements
Requirements
- Bachelor's degree in Computer Science, Data Science, or a related field.
- 5-6 years of experience in AI/ML engineering, data science, or a closely\n related software engineering discipline
- Demonstrated experience building and deploying production AI or ML systems
- Hands-on experience with cloud-based AI platforms
- Proficiency with Snowflake AI tooling and Cortex capabilities, Amazon\n Bedrock, AWS SageMaker, and ECS for AI/ML workloads
- Hands-on experience with agentic frameworks: Snowflake Intelligence,\n LangGraph, LangChain, AutoGen, or CrewAI
- Strong Python skills including experience with ML libraries and API\n development
- Experience with LLM orchestration, prompt engineering, and RAG patterns
- Familiarity with CI/CD pipelines and MLOps best practices
- Understanding of responsible AI principles, model governance, and data\n privacy standards
- Strong communication skills with ability to explain complex AI concepts to\n non-technical stakeholders
Nice-to-haves
- Master’s degree in Machine Learning, AI, Computer Science, Statistics is a\n plus.
- Experience in a corporate or enterprise environment preferred
- AWS certifications (ML Specialty, Solutions Architect, or Developer)
- Experience with multi-agent system design and orchestration at scale
- Exposure to hospitality, travel, or cruise industry environments
- Familiarity with Snowflake data sharing and S3-based data export\n patterns
Benefits
- Cost-effective medical, dental and vision plans
- Employee Assistance Program and other mental health resources
- Additional programs include company paid term life insurance and disability\n coverage
- 401(k) plan that includes a company match
- Employee Stock Purchase plan
- Holidays – All full-time and part-time with benefits employees receive days\n off for 8 company-wide holidays, plus 2 additional floating holidays to be\n taken at the employee’s discretion.
- Vacation Time – All full-time employees at the manager and below level\n start with 14 days/year; director and above level start with 19 days/year.
- Part-time with benefits employees receive time off based on the number of\n hours they work, with a minimum of 84 hours/year. All employees gain\n additional vacation time w