Seeking a Lead, AI Engineer to set engineering standards for Gen AI across Royal Caribbean Group and lead delivery of projects spanning multiple brands and business functions. The role involves using agentic coding tools, defining testing/evaluation practices, and building prototypes with business users.
Responsibilities
Set engineering standards for Gen AI across Royal Caribbean Group
Lead delivery of projects that span multiple brands and business functions
Build prototypes with business users
Design, build, and maintain skills, plugins, slash commands, subagents, hooks, and MCP servers
Publish engineering standards as living, agent-readable instructions
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field
The AI Engineer is responsible for building and deploying AI agents (Microsoft Copilot and Claude) and private retrieval-augmented generation (RAG) applications.
Compensation
Base salary: $110,000 + 10% bonus
Responsibilities
Design, build, and deploy AI agents using Microsoft Copilot Studio and Claude (Anthropic), or apply ML experience to similar enterprise use cases
Implement RAG applications using vector databases (such as Pinecone, Weaviate, Azure AI Search, Chroma) including ingestion, chunking, embeddings, retrieval, and evaluation
Help configure deployments to meet enterprise requirements for data isolation, security, and governance
Work with business, data, and product teams to turn requirements into practical AI agent or RAG/ML solutions
Support management of the data layer—databases and pipelines—underlying agents and RAG/ML applications
Requirements
Bachelor’s degree in Information Technology, Computer Science, or a related field
As a Technical Solution Architect, become a part of a cross-functional development team engineering experiences of tomorrow, focusing on AI transformation and replacing manual decision-making workflows with reliable, auditable AI-assisted systems.
Lead the design, implementation, and operation of data infrastructure for agentic, LLM‑based AI solutions within Roche Digital Technology’s Applied AI Engineering Team.
Responsibilities
Collaborate with AI engineers, data scientists, product owners, and developers to integrate LLMs into scalable, robust, fair, and ethical end‑user applications.
Design and implement scalable, high‑performance data pipelines for AI/GenAI applications, ensuring efficient ingestion, transformation, storage and retrieval.
Work with vector databases such as AWS OpenSearch and Azure AI Search to enable similarity search and RAG for generative AI.
Build and maintain cloud‑based data solutions using AWS (OpenSearch, S3, Lambda) or Azure (AI Search, Blob Storage).
Design and optimize data storage and processing using Snowflake for scalable, cloud‑native analytics.
Requirements
Bachelor's degree in Computer Science, Data Engineering or related fields
Design the foundation that makes intelligent systems scale for our enterprise.
Compensation
Base Pay Range: $200,000 to $260,000 annually
An annual employee bonus program
Responsibilities
Define the end-to-end reference architecture for AI and data/storage systems across Azure AI Foundry, Azure AI Services, Azure AI Search, Azure Databricks/Fabric, and Snowflake.
Design integration blueprints for RAG workflows, data pipelines, agentic frameworks, and our enterprise GPT solution.
Establish standards for model deployment, versioning, prompt management, and telemetry within Azure AI Foundry.
Build and maintain scalable cloud environments for model training, evaluation, and inference.
Oversee vector database design (Azure AI Search or equivalent) and integration with Snowflake/Fabric data hubs.
Serve as the primary architect and guardian of the Artificial Intelligence ecosystem, responsible for end-to-end security of AI architectures within Azure.
Compensation
Base Salary Range: $172,780 to $225,720 annually. An annual employee bonus program
Responsibilities
Design and implement secure-by-design architectures for the entire AI lifecycle, including data ingestion, model training, fine-tuning, and inference.
Lead the security configuration for Azure OpenAI Studio, Azure AI Foundry, and Azure AI Search.
Develop and deploy security controls, including prompt injection mitigations, rate limiting, and content filtering.
Securely implement and oversee Model Context Protocol (MCP) to facilitate safe communication between AI models and local/remote data sources.
Establish and maintain AI security standards based on global frameworks (e.g., NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLMs).
Support the development, testing, and documentation of AI-enabled applications using the Microsoft Azure stack.
Compensation
The hourly rate for this position is based on the level of education at the time the intern program begins: Sophomore $18.00 Junior $22.00 Senior (or May 2028 graduate) $22.00 Current graduate/law student $25.00
Responsibilities
Develop a focused AI solution using Python, REST APIs, Azure SDKs, Azure OpenAI, Azure MCP and Microsoft Foundry.
Assist with prompt engineering, structured outputs, tool calling, AI agents, and retrieval-augmented generation solutions.
Build or support integrations with Azure AI Search, Azure Storage, Azure SQL, Cosmos DB, and approved enterprise APIs.
Prepare and validate approved data for AI use cases, including document chunking, metadata creation, embeddings, and search indexing.
Create unit, integration, and AI evaluation tests covering accuracy, relevance, groundedness, safety, and edge cases.
Requirements
Enrollment in an associate’s, undergraduate or graduate program at a college or university is required. Recent graduates are not eligible for our Developmental Internship program.
Lead the design and governance of enterprise-wide Generative AI architecture, defining strategy, standards, and best practices for scalable, secure, and responsible AI solutions across cloud-native environments.
Responsibilities
Define enterprise-wide Generative AI architecture strategy, standards, and best practices
Design scalable and secure LLM-powered solutions using Azure OpenAI and Azure AI Services
Architect enterprise-grade RAG platforms leveraging vector databases, semantic search, and knowledge management systems
Design and govern Agentic AI ecosystems utilizing AI Agents, tool calling, orchestration, and autonomous workflows
Evaluate and select appropriate foundation models, embeddings, and multimodal architectures
Requirements
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field
Nice to have: Microsoft Certified: Azure Solutions Architect Expert
Nice to have: Microsoft Certified: Azure AI Engineer Associate
Nice to have: Microsoft Certified: Azure AI Fundamentals
Nice to have: Experience working with Fortune 500 enterprise AI transformation programs
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