AI Engineer

Aspen Skiing Company•Denver, CO

5d•$103,000 - $144,000•Hybrid

About The Position

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.

Requirements

Bachelor’s degree or equivalent experience in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field
Three or more years of experience in software engineering, AI/ML development, data engineering, or a related technical role, with demonstrated experience shipping solutions to production
One or more years of hands-on experience building with AI or machine learning technologies, including LLMs, AI agents, automation workflows, or applied ML systems
Demonstrated experience deploying AI or software solutions in a production environment, beyond notebooks, prototypes, and academic projects
Experience working in or closely with enterprise IT environments, including Microsoft/Azure ecosystems, preferred
Strong proficiency in Python, with experience writing clean, maintainable, production-quality code
Hands-on experience with LLM APIs and AI services (e.g., Azure OpenAI, Anthropic Claude, OpenAI) including prompt engineering, function/tool calling, and model integration patterns
Working knowledge of AI application frameworks such as LangChain, Semantic Kernel, or similar tools for building LLM-powered applications and agent workflows
Experience with data engineering fundamentals: SQL, data pipelines, ETL processes, and working with relational databases, data warehouses, or cloud data platforms
Familiarity with cloud platforms and services, particularly Microsoft Azure (Azure AI, Azure Functions, Azure DevOps), with the ability to architect, deploy, and manage cloud-based AI workloads
Working knowledge of REST APIs, Git, CI/CD practices, and software development lifecycle fundamentals
Experience with or willingness to learn Copilot Studio for low-code AI development and business process automation
Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and semantic search patterns
Strong problem-solving mindset with the ability to independently evaluate technical options, make pragmatic decisions, and move quickly from concept to working solution
Ability to communicate technical concepts clearly to non-technical stakeholders and collaborate effectively with business teams, project managers, and IT partners
Comfort with ambiguity and an entrepreneurial mindset. This is a build-from-scratch role where tools, patterns, and processes will evolve as the program matures
Working knowledge of data privacy principles, enterprise data classification standards, and how these apply to AI model inputs, training data, and outputs
Awareness of AI-specific security risks (e.g., prompt injection, data leakage through model outputs, pipeline integrity) and data privacy regulations applicable to the business (e.g., CCPA, state privacy laws), with an understanding of how these constrain AI system design, particularly regarding customer data use in model inputs and output.
Ability to stay current with the rapidly evolving AI landscape for new models, tools, frameworks, and best practices. Bring informed recommendations to the Head of AI on opportunities to improve platform capabilities and project delivery

Responsibilities

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 iteration
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 standards
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 repeatable
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