Artificial Intelligence Engineer

Ryan Companies•Minneapolis, MN

1d•Hybrid

About The Position

Ryan Companies US, Inc. is hiring an Artificial Intelligence Engineer for its growing Data and Artificial Intelligence team. Reporting directly to the Director of AI, this high-impact role is embedded with construction project teams and serves as the technical bridge between enterprise AI capabilities and everyday jobsite workflows. The engineer will work alongside Project Managers, Superintendents, Project Engineers, and Field Operations to identify operational friction points and rapidly prototype, integrate, and deploy AI solutions that create value in construction delivery. This is an in-office role at Ryan’s Minneapolis headquarters four days per week, with one day working from home. The position also requires weekday travel to construction sites, likely four to five days per month, mostly in the Midwest. The role calls for hands-on AI engineering and coding, Google Cloud Platform expertise, a product-focused mindset, and a willingness to work on active construction sites. The engineer will develop scalable software, agentic workflows, and field technology tools; build RAG applications and autonomous agents for construction documents; integrate solutions with construction platforms and data systems; and relay field feedback to the centralized AI team so successful prototypes can scale across the enterprise. The position also contributes to Ryan’s data and AI culture by promoting data-driven decision-making.

Requirements

At least 3 years of hands-on experience building and deploying generative AI, machine learning, or advanced software solutions in enterprise or field environments.
Advanced proficiency and hands-on workflow mastery with agentic coding environments and AI harnesses such as Cursor, Claude Code, Codex, or comparable tools.
Experience architecting and deploying applications and agents on Google Cloud Platform, including Agent Engine (Vertex AI), Cloud Run, Cloud Composer/Dataflow, and IAM security models.
Experience developing custom RAG pipelines, fine-tuning LLMs, working with vector databases, and orchestrating multi-agent systems.
Strong coding proficiency in Python, SQL, and TypeScript/JavaScript; understanding of RESTful APIs, data serialization, and Git workflows.
Ability and willingness to travel regularly to active construction sites, participate in jobsite meetings, and learn field operations.
Bachelor’s degree in Computer Science, Data Science, Software Engineering, Construction Engineering, or equivalent practical experience.
Strong problem-solving skills and ability to communicate effectively with technical and non-technical audiences.
Collaborative approach and ability to work with people with diverse skill sets and work styles.
Resourceful, entrepreneurial, and innovative mindset, including the ability to address ambiguous challenges.
Commitment to staying current with AI trends and applying them to deliver business value.
Understanding of ethical and responsible AI principles and practices.

Nice To Haves

Prior exposure to Architecture, Engineering, and Construction (AEC), commercial real estate, or industrial operations.
Familiarity with construction tools and APIs such as Procore, Autodesk BIM 360/ACC, Bluebeam, and DroneDeploy.
Experience designing conversational interfaces or automated field data capture workflows, such as voice-to-text or field forms.

Responsibilities

Embed with construction project teams to observe, diagnose, and address jobsite operational challenges using AI and automation.
Use agentic coding environments to build, test, and iterate on functional prototypes.
Write scalable, robust, and maintainable code for tailored applications, agentic workflows, and field technology tools.
Design, configure, and maintain production solutions on Google Cloud Platform, including services such as Agent Engine (Vertex AI), Cloud Run, BigQuery, and Cloud Storage.
Build and deploy Retrieval-Augmented Generation applications and autonomous agents to query construction documents, including drawings, specifications, submittals, RFIs, and change orders.
Integrate solutions, models, and pipelines with construction ecosystems such as Procore, Autodesk Construction Cloud, ERPs, and document repositories.
Relay jobsite feedback to the centralized AI team and help turn field-tested prototypes into scalable enterprise solutions.
Promote data-driven decision-making and help foster Ryan’s data and AI culture.