AI Engineer - On Site

K Group Companies

$100K — $120K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Hands-on expertise in AI/automation platforms like n8n and API development.
  • Proficiency with Python and integration patterns with platforms like Microsoft 365 and SharePoint.
  • Experience in building production-grade systems with a focus on reliability and documentation.
  • Strong communication skills to present technical work to non-technical stakeholders.
  • Ability to work autonomously within a strategic framework; decision-making is part of the role.
  • Background in managed service providers (MSP) or technology services is preferred.

Responsibilities

  • Design and maintain AI-powered automation workflows using tools like n8n and Python.
  • Develop systems for AI classification, compliance, and automated monitoring.
  • Implement AI architectures supporting multiple LLM providers with configurable thresholds.
  • Lead client delivery engagements, managing implementation and optimization processes.
  • Translate business requirements into functional systems, presenting results to stakeholders.
  • Build frameworks and documentation to scale AI consulting engagements efficiently.
  • Support AI adoption by creating training materials and tracking relevant metrics.

Benefits

  • Opportunity to work in a cutting-edge AI and Automation practice.
  • Exposure to both internal and external client engagements.
  • Hands-on experience translating business needs into practical solutions.
  • Collaboration with a dedicated AI Enablement Team and leadership.
  • Ability to contribute to impactful AI frameworks and governance efforts.
Full Job Description
Role Overview

The AI Automation Engineer is a core technical delivery resource within K Group's AI and Automation practice. Working alongside the AI Enablement Team and practice leadership, this role leads the design, build, and ongoing optimization of AI-powered solutions for both internal operations and external client engagements. The engineer translates scoped strategy into production-grade systems, contributes to internal adoption efforts, and helps build the repeatable frameworks that allow the practice to scale.

This is a builder role first. The ideal candidate thrives on turning complex business requirements into working, measurable systems - and takes pride in delivering solutions that are practical, responsible, and built to last.

Core Responsibilities

Automation & Workflow Engineering
  • Design, build, and maintain AI-powered automation workflows using n8n, Python, and integrated APIs including ConnectWise, Microsoft 365, SharePoint, and others.
  • Develop intelligent systems including multi-stage AI classification pipelines, automated compliance and billing review processes, and notification-driven monitoring tools.
  • Implement provider-abstracted AI architectures supporting OpenAI, Ollama, and other LLM providers with configurable confidence thresholds and fallback logic.
  • Build and iterate on internal tools that reduce manual effort, improve data accuracy, and create measurable operational efficiencies.

Client Delivery & Engagement Support
  • Lead delivery execution for AI/automation client engagements - managing implementation, iteration, and ongoing optimization through to completion in coordination with the practice team.
  • Participate in client discovery sessions as a technical resource, contributing to needs assessment, feasibility evaluation, and solution design under the direction of practice leadership.
  • Translate scoped business requirements into working systems and present delivery results to client stakeholders including operations leads and project sponsors.
  • Build reusable delivery frameworks, templates, and documentation that allow AI consulting engagements to scale efficiently across multiple clients.


Enablement & Adoption
  • Support AI adoption across internal teams by building training materials, playbooks, and purpose-built tools that make AI accessible to non-technical staff.
  • Track and report on AI adoption metrics, connecting usage data to business outcomes rather than vanity metrics.
  • Contribute to responsible AI use and utilization efforts - including Microsoft 365 Copilot - supporting the governance frameworks and usage guidelines established by practice leadership.

What Success Looks Like - Year One

To be defined collaboratively with leadership. Initial indicators may include:
  • Production-grade automation workflows deployed for internal K Group operations.
  • Client delivery engagements completed on time and within scope with documented outcomes.
  • Reusable delivery frameworks and templates in place for at least two service offering types.
  • AI adoption metrics established and actively tracked across internal teams.
  • Contributed to AI utilization efforts, including Microsoft 365 Copilot, with adoption measurably improving across internal teams.

Experience & Qualifications
  • Hands-on expertise in AI/automation platforms - n8n, LLM integrations, workflow orchestration, API development.
  • Proficiency with Python and modern integration patterns across business platforms including ConnectWise, Microsoft 365, and SharePoint.
  • Experience building production-grade systems - not just proof-of-concept tools - with attention to reliability, documentation, and maintainability.
  • Strong communicator capable of presenting technical work and outcomes to non-technical stakeholders.
  • Comfortable working within a defined strategic framework while exercising autonomy in execution and delivery decisions.
  • MSP or technology services background preferred.

Reporting & Structure

Reports to: Director of Engineering

Team: AI Enablement Team

Location: Grand Rapids, MI

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