AI Automation & Solutions Lead

The Arcticom Group•Denver, CO

8d•Remote

About The Position

The Arcticom Group (“TAG”) is a U.S.-based network of commercial and industrial mechanical services companies that provide HVACR service, maintenance, and installation services throughout North America. TAG is committed to being an “employer of choice” and ensuring employees have a home where they can learn and grow. With competitive compensation and an attractive benefits package, TAG is an exciting place to work. The Arcticom Group (TAG) is seeking a highly technical, execution-oriented AI Automation & Solutions Lead to design, develop, and deploy intelligent agents and automated workflows. In this role, you will sit at the intersection of technology and business operations. You will take defined operational requirements and use cases, and design semantic models, orchestrated workflows, and AI‑driven solutions that make our teams faster, smarter, and more efficient. You won’t just be recommending tools; you will be the primary builder of TAG’s automated future, owning the modeling, orchestration, and transformation layers that power AI‑enabled business processes, while coordinating closely with external AI partners and internal stakeholders.

Requirements

Experience: 7+ years of experience in technical operations, software engineering, data engineering, or systems architecture.
Technical Literacy: Hands‑on experience designing semantic data models , building automated workflows, and working with orchestration and transformation tools. Comfort working with structured and semi‑structured data, automation platforms, and scripting languages (e.g., Python or JavaScript). Experience with AI agent frameworks is required.
Partner Management: Proven success collaborating with external technology vendors, consultants, or distributed development teams.
Operational Excellence: Deep understanding of how data, workflows, and decisions move through an organization.
Execution‑Oriented: Demonstrated ability to move initiatives from concept to deployed solutions with real user adoption.

Nice To Haves

Deep familiarity with mechanical services, dispatch operations, and skilled‑trade environments.
Proven ability to apply AI through workflow orchestration and intelligent automation to improve technician productivity and operational efficiency.
Demonstrated success driving digital transformation across decentralized, field‑based workforces by translating complex data and AI concepts into practical, easy‑to‑use tools.

Responsibilities

Automation & Agent Development Transform documented business requirements and operational use cases into deployed AI agents, bots, and orchestrated workflows .
Design and maintain semantic data models that represent business concepts, operational context, and decision logic used by AI‑enabled systems.
Build and manage workflow orchestration and data transformation layers that connect operational systems, automation platforms, and AI models.
Leverage advanced automation, orchestration, and transformation tools (e.g., low‑code/no‑code automation platforms, enterprise RPA, data transformation frameworks) to eliminate manual data entry and streamline dispatch, routing, and compliance reporting.
Vendor & Consultant Partnership Act as the primary technical liaison for third‑party AI providers, software vendors, and external technology consultants.
Evaluate and integrate externally developed AI solutions into TAG’s technology ecosystem, ensuring alignment with established semantic models, orchestration standards, and data architecture .
Manage technical deliverables from external partners, ensuring solutions meet TAG’s architectural, governance, and security standards.
Cross-Functional Execution & Deployment Partner closely with department leaders to pilot, test, and deploy orchestrated AI‑enabled process improvements without disrupting daily operations.
Champion adoption of newly built systems through rigorous QA testing, effective change management, training, and clear technical documentation.
Serve as the translator between business objectives and technical execution, setting clear expectations and deployment timelines.
Data Governance & Optimization Establish data governance best practices to ensure information flowing through semantic models, transformation pipelines, and automated workflows is clean, structured, and secure.
Monitor performance, scalability, and cost‑efficiency of implemented automation and AI solutions, continuously refining semantic models and orchestration logic based on measurable outcomes.