AI Engineer at AspenSkiingCompany

Position Summary The AI Engineer designs, builds, and deploys production-grade AI solutions that drive measurable business value across Aspen One. This role is responsible for translating business needs into working AI systems which includes integrating large language models, building intelligent agents and automated workflows, connecting enterprise data sources, and standing up the reusable platform infrastructure that allows AI capabilities to scale across the organization. The AI Engineer partners closely with the Sr. Director Data and Digital Technology, the AI Program Manager, IT Systems, Digital teams, and Cybersecurity to deliver AI-powered solutions while simultaneously building the technical foundation that makes future projects faster, more secure, and more supportable. This position reports to the Senior Director, Data & Digital Technology. The salary range for this position is $103,000 - $140,000. Actual pay will be dependent on budget and experience; all our salaried roles are eligible for bonus.  Applications for this position will be accepted until April 19, 2026.   Essential Job Functions / Key Job Responsibilities AI Solution Development • Design, build, and deploy AI-powered solutions using large language models, AI agents, and automation workflows, and other software development tools that address real business problems across Aspen One’s operations and business units,, guest experience, and corporate functions • Develop and maintain integrations between AI models (e.g., Azure OpenAI, Anthropic Claude) and enterprise systems, APIs, databases, and business workflows • Build retrieval-augmented generation (RAG) systems, prompt engineering frameworks, and agent architectures that connect AI to proprietary data sources for accurate, grounded responses • Develop and extend solutions within Microsoft Copilot Studio, Power Platform, and other low-code/no-code AI tools where appropriate, while building custom solutions on platforms such as Azure AI Studio when platform limitations require it • Build AI solutions across the full platform spectrum, choosing the right platform for the job. This includes low-code tools like Microsoft Copilot Studio and Power Platform for rapid business automation, to custom-built applications using Azure, OpenAI, Azure AI Studio, Azure Functions, and frameworks like Semantic Kernel or LangChain. • Own the full development lifecycle for AI software development projects: requirements analysis, solution design, development, testing, deployment, and post-launch monitoring and iterationPlatform & Infrastructure • Build and maintain reusable platform components that make future AI projects faster and more consistent, including model orchestration layers, shared prompt libraries, authentication and access control patterns, and deployment templates • Establish and manage the AI software development lifecycle (SDLC): development, testing, staging, and production environments with appropriate version control, CI/CD, and release processes • Implement monitoring, logging, and quality assurance frameworks for AI solutions in production, including tracking for model performance, drift, usage patterns, and error rates • Support model selection and orchestration decisions, evaluating different AI models and services for specific use cases based on capability, cost, latency, and data handling requirements • Partner with Cybersecurity and IT to ensure AI platform components meet security, identity, and access control requirements, including data classification and governance standardsData Readiness & Engineering • Connect enterprise data sources to AI systems, including databases, data warehouses, APIs, and document repositories, ensuring data is structured and accessible for AI consumption • In partnership with the data engineering team, design and build data pipelines that prepare, transform, and deliver data to AI models, with particular focus on customer data domains and operational systems • Work with data owners and IT teams to identify data quality issues, define data requirements for AI projects, and implement data access patterns that are secure, efficient, and repeatableTechnical Partnership & Collaboration • Partner with the AI Program Manager on technical scoping, feasibility assessments, effort estimates, and solution design for AI projects across the portfolio • Collaborate with IT Systems, Digital teams, and business stakeholders to understand requirements, design solutions that integrate with existing workflows, and support user acceptance and adoption • Contribute to security and governance reviews in partnership with Cybersecurity, including evaluating AI vendors and platforms for data handling practices, risk posture, and compliance requirements • Provide technical guidance and support to teams exploring AI tools and solutions, including Copilot Studio users, business-led automation efforts, and the broader AI community of practice • Other duties as assigned