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AI Automation & Agentic Systems Specialist

Part-Time | Opportunity to Grow into Full-Time

About the Role

We are an established MSP and marketing firm looking for an AI Automation & Agentic Systems Specialist to help us transform the way our company—and eventually our clients—operate using AI.

This is not a traditional IT support role or a position focused simply on using ChatGPT. We are looking for someone who can analyze real-world business processes, identify opportunities for automation, and design agentic AI systems that can perform work across business applications while keeping a human in the approval loop for important actions.

The initial focus of this position will be internal.

You will work directly with company leadership to understand our day-to-day operations, identify repetitive and time-consuming tasks, and implement AI agents and automated workflows that improve efficiency without sacrificing oversight or control.

Once we have successfully implemented and proven these systems internally, the role will expand into helping us productize and deploy Agentic AI solutions for our existing MSP and marketing clients.

Several of our clients are already asking for assistance implementing AI automation, making this an opportunity to help build a new service offering from the ground up.

This position will begin part-time with the expectation that it can grow into a full-time role as client demand increases.

What You'll Be Doing

Business Process Discovery & Optimization

• Work directly with leadership and employees to understand existing business processes.
• Identify repetitive, manual, administrative, and operational tasks that can be automated or AI-assisted.
• Map existing workflows and identify bottlenecks, unnecessary steps, and opportunities for improvement.
• Prioritize automation projects based on business impact, complexity, risk, and ROI.
• Recommend when AI should—and should not—be used to solve a problem.

Agentic AI Development

Design and implement AI agents capable of completing multi-step business processes such as:

• Email triage, drafting, and follow-up
• CRM updates and data entry
• Meeting preparation and follow-up
• Customer onboarding
• Ticket classification and routing
• Internal documentation
• Reporting and data analysis
• Marketing workflow automation
• Lead qualification and follow-up
• Proposal and document generation
• Task creation and project management
• Research and information gathering
• Recurring administrative processes

Agents should be capable of gathering information, reasoning through tasks, interacting with business applications, and preparing actions for execution.

Human-in-the-Loop Approval

A core requirement of our AI strategy is maintaining appropriate human oversight.

You will design workflows where AI can perform the majority of the work while requiring human approval before sensitive or consequential actions are completed.

Examples could include:

AI prepares an email → leadership reviews → AI sends

AI prepares a proposal → leadership approves → proposal is delivered

AI identifies a CRM update → employee approves → CRM is updated

AI recommends an operational action → management approves → automation executes

The goal is to automate as much of the repetitive work as possible while maintaining accountability and control.

AI & Business Systems Integration

Build integrations between AI systems and the applications our company and clients already use.

Depending on the environment, this may include:

• Microsoft 365
• Google Workspace
• CRM platforms
• PSA/RMM platforms
• Ticketing systems
• Marketing platforms
• Project management systems
• Accounting systems
• APIs and webhooks
• Databases and internal knowledge bases
• Automation platforms such as n8n, Make, Zapier, or Power Automate
• LLM and AI platforms from OpenAI, Anthropic, Microsoft, Google, and others

We are not committed to one specific AI platform. We want someone who understands the ecosystem and can recommend the right architecture for each situation.

Building Our Client AI Service

After successfully implementing AI automation internally, you will help us develop a repeatable Agentic AI service offering for our clients.

Responsibilities will eventually include:

• Conducting AI automation discovery sessions with clients.
• Mapping client business processes.
• Identifying high-value automation opportunities.
• Designing AI agents and workflows.
• Creating approval and governance processes.
• Integrating AI with client business applications.
• Testing and deploying AI solutions.
• Training client employees.
• Monitoring and improving deployed agents.
• Documenting solutions so they can be supported by our MSP team.
• Helping establish standardized AI implementation packages and recurring managed AI services.

The long-term opportunity is to help us build the systems, standards, and methodology behind a growing AI Automation / Agentic AI practice.

What We're Looking For

The ideal candidate combines business-process thinking with hands-on technical ability.

You should be comfortable sitting with a business owner or employee, asking questions about how they perform their job, identifying inefficiencies, and then translating those requirements into a working AI-powered solution.

We are particularly interested in candidates with experience in several of the following areas:

• Agentic AI systems
• Large Language Models (LLMs)
• OpenAI / Azure OpenAI
• Anthropic Claude
• Microsoft Copilot ecosystem
• AI APIs
• n8n
• Make
• Zapier
• Microsoft Power Automate
• API integrations
• Webhooks
• Python and/or JavaScript
• REST APIs
• JSON
• Databases
• Retrieval-Augmented Generation (RAG)
• Vector databases / semantic search
• AI tool/function calling
• Multi-agent workflows
• MCP or similar AI integration protocols
• Prompt and context engineering
• AI evaluation and testing
• Business process automation

Experience working with MSPs, IT service providers, marketing agencies, or SMB technology environments is a significant plus.

Security & Governance

Because these systems may interact with sensitive company and client information, security must be built into every implementation.

The successful candidate should understand or be willing to develop expertise around:

• Role-based access and least-privilege permissions
• Data privacy
• Credential and API-key management
• AI data governance
• Logging and audit trails
• Human approval controls
• Error handling and rollback procedures
• AI hallucination and reliability risks
• Testing AI systems before production deployment
• Separating client environments and data
• Monitoring AI agents after deployment

We want to move quickly with AI while maintaining the security and operational standards expected from a professional managed services provider.

What Success Looks Like

Within the first several months, we would expect this person to:

1. Learn how our company operates.
2. Develop an inventory of potential AI automation opportunities.
3. Prioritize opportunities based on impact and feasibility.
4. Build several internal AI agents and automated workflows.
5. Demonstrate measurable time savings or operational improvements.
6. Establish standards for human approval, security, testing, and documentation.
7. Create reusable architectures and templates.
8. Help turn successful internal implementations into solutions we can offer our clients.

Over time, this individual could become responsible for helping lead our AI Automation and Agentic AI service offering.

Position Structure

Initial Status: Part-Time

Growth Opportunity: Full-Time as internal initiatives and client demand increase

This position is ideal for someone who wants more than a traditional automation-development job. You will have the opportunity to help determine our AI strategy, build solutions from the ground up, and ultimately help create a new technology service offering that can be deployed across our client base.

The Person We're Looking For

We value curiosity and practical problem-solving over simply knowing the latest AI terminology.

We're looking for someone who sees a repetitive five-step business process and immediately starts thinking:

"How much of this could an AI agent handle, where should a person remain involved, and how can we make the entire process faster and more reliable?"

If you enjoy combining AI, automation, APIs, business operations, and creative problem-solving—and want the opportunity to help build an Agentic AI practice from its earliest stages—we'd like to hear from you.