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AI Integration & Automation Engineer
Job in
Inver Grove Heights, Dakota County, Minnesota, 55077, USA
Listed on 2026-08-28
Listing for:
Mauer Automotive
Full Time
position Listed on 2026-08-28
Job specializations:
-
Software Development
AI Engineer (Applied/Software)
Job Description & How to Apply Below
This is a builder-first, hands-on-keyboard role. You should know how to code rapidly prototyping and shipping working applications with AI coding tools rather than writing everything from scratch while still knowing enough to secure, maintain, and version-control what you build (using Git Hub as the backbone for all code and configuration). You'll be fluent across multiple AI platforms and vendors, know which tool fits which job, and be comfortable owning something from idea to internal production use.
Key Responsibilities AI Application & Agent Development Build internal applications, tools, and AI agents using a multi-vendor stack Claude, Git Hub (Copilot and Actions), Lovable, ChatGPT, and others deliberately avoiding lock-in to any single provider and combining tools to fit each use case.
Vibe code working prototypes and production internal apps quickly with AI coding tools, then harden, test, and maintain them for real day-to-day use across stores.
Use Git Hub as the backbone for version control, code review, and CI/CD across every application and integration built regardless of which AI platform generated the original code.
Continuously market-check the AI and developer-tool landscape (new models, coding platforms, agent frameworks, vendors) and bring in or swap tools as better options emerge, rather than defaulting to whatever's already in place.
Design and deploy AI agents embedded directly in operational workflows e.g., lead follow-up, service scheduling, inventory alerts, F&I document prep so they run with minimal manual intervention.
Data Infrastructure & Secure Connections Build and maintain secure, reliable connections between the DMS, CRM, and Mauer's internal data lake, so data from every store flows into one governed source.
Structure and maintain the data lake so it's usable as a foundation for AI-built applications and agents clean schemas, reliable pipelines, sensible access boundaries.
Ensure all data connections (DMS - CRM - data lake - AI tools) are encrypted, access-controlled, and monitored for reliability and integrity.
Automation & Integration Development Design and build automation workflows (Zapier, Make, Power Automate, or custom scripts) and AI agents that connect systems across the group leads, inventory, service scheduling, follow-up communications, F&I, and marketing platforms.
Build and maintain API integrations between the DMS/CRM, the internal data lake, and third-party AI tools, ensuring data flows cleanly and reliably in all directions.
Write and maintain scripts and small applications (Python, JavaScript, SQL) for data pulls, reporting, custom connectors, and process automation.
Develop internal tools, dashboards, and reports built on the data lake to support store managers and leadership.
Troubleshoot broken integrations, agents, and automations across the store network, diagnosing root cause (API changes, data mismatches, tool updates) and fixing quickly to minimize downtime.
AI Tool Lifecycle:
Build, Replace & Maintain Own the ongoing health of the group's AI application, agent, and tool stack across vendors (Claude, Git Hub, ChatGPT, Lovable, and others) monitor performance, uptime, and output quality.
Proactively evaluate the market across multiple vendors for better-fit AI tools and platforms, and lead migrations when an existing tool is underperforming, outdated, or being replaced by something stronger deliberately keeping the group multi-vendor rather than locked into one provider.
Rebuild or re-architect automations and integrations as underlying tools, APIs, or vendors change, so workflows keep working without disruption to store operations.
Maintain documentation of every AI tool, integration, and automation in use configuration, ownership, dependencies, and renewal/replacement timelines.
Establish a lightweight testing/QA process before pushing any new tool, replacement, or automation change live across stores.
Training & Adoption Train dealership staff on new AI/automation tools; create simple documentation and SOPs.Serve as the go-to internal resource for "can we automate this?" questions across departments.
Data & Reporting Build and maintain dashboards (e.g., Power BI, Google Data Studio, Smartsheet) pulling from sales, service, and marketing data sources.
Monitor AI tool performance (chatbot conversion, response times, lead-to-sale impact) and report ROI to leadership.
Security & Governance Own security for the data lake and all AI…
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