Mauer Automotive Group is seeking an AI Integration & Automation Engineer to build internal applications, agents, and workflows using a best-of-breed stack of AI and development platforms Claude, GitHub, Lovable, ChatGPT, and others choosing and combining whichever tools solve the problem best rather than standardizing on one vendor. You'll also build and secure the data infrastructure those tools run on: a unified connection between our DMS, CRM, and an internal data lake, which becomes the foundation for everything you build. 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 GitHub 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, GitHub (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 GitHub 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, GitHub, 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 tools/integrations: manage API keys and credentials, enforce least-privilege access, and rotate/revoke access when tools, vendors, or staff change. Set up and monitor access controls for every connected system (DMS, CRM, data lake, marketing platforms, AI vendors) to prevent unauthorized data exposure. Vet new AI vendors and tools for data-handling practices before integration; flag and resolve security gaps in existing tools. Ensure AI tools comply with data privacy and customer communication regulations (TCPA, CAN-SPAM, state-level auto dealer rules).

Maintain an incident-response habit:

know how to quickly disable a compromised integration or tool and contain any data exposure Required Qualifications 2-5 years of experience in a technical, analyst, or automation-focused role (automotive retail experience a plus, not required). Deep, hands-on fluency with major AI platforms (Claude, ChatGPT, Lovable, and similar) able to choose the right tool for a given use case and get productive with new ones quickly, without favoring a single vendor by default. Proven ability to code building and shipping working applications with AI coding assistants plus the underlying skill to review, secure, and maintain what's generated. Data engineer, specifically cloud data engineer with experience in Azure . oversee the in-house app, software development would be preferable experience. Solid working knowledge of GitHub (repos, branching, pull requests, Actions/CI) as the version-control backbone for AI-generated and hand-written code alike. Working proficiency in at least one scripting language (Python or JavaScript preferred). Hands-on experience building and maintaining API integrations and automation platforms (Zapier, Make, Power Automate, or custom-coded connectors). Experience working with or building data pipelines/data lakes, and connecting them as a foundation for downstream applications or AI agents. Working knowledge of access management and credential security (API keys, OAuth, least-privilege access) across multiple connected systems and vendors. Comfortable with SQL and basic data analysis/reporting. Strong communication skills able to translate technical capability into plain-language business value for non-technical staff and GMs. Preferred Qualifications Experience with a dealer management system (DMS) or automotive CRM. Experience building or maintaining a data lake / data warehouse and connecting it to applications or AI agents. Experience building AI agents or agentic workflows (e.g., Claude, ChatGPT/GPTs, LangChain, or similar frameworks). Experience setting up GitHub Actions or other CI/CD pipelines to deploy AI-built applications. Experience building internal tools or dashboards (Power BI, Smartsheet, Retool, or similar). Prior experience training or supporting non-technical staff on new software.