AI Automation Engineer

Monument Consulting • Richmond, VA

1d

About The Position

Monument is seeking an internal AI Automation Engineer to build agents and automations used by its operations, finance, HR, and sales support teams. The role works directly with internal function owners to observe how processes are actually performed, identify manual work, and determine whether to automate, simplify, consolidate, or discontinue it. The primary platform is Microsoft, including Copilot Studio, Power Automate, Power Apps, Dataverse, and Microsoft 365, though other solutions may be proposed when appropriate. Success is measured by adoption and measurable operational results, not simply by delivery; the engineer monitors usage, improves or retires solutions, and ensures they can be maintained by their owners.

The work generally involves observing a process, documenting its steps and exceptions, assessing its value for automation, shipping a small working solution to real users, and instrumenting and handing it over. Solutions should be delivered quickly and embedded in tools users already work in, such as Teams, Outlook, and SharePoint. The engineer builds conversational agents, automations, and applications; integrates existing systems; writes code where low-code tools are insufficient; tests real-world cases; trains users; and maintains delivered solutions.

The role also contributes reusable components and patterns to an internal library, raises governance and data-handling concerns, and helps assess new Microsoft platform capabilities. Compensation is USD $110,000–$135,000 per year.

Requirements

• 3–5 years building business applications, integrations, or automations used daily by real people.
• Hands-on Microsoft Power Platform delivery experience, including Power Automate and Power Apps at minimum.
• Working knowledge of Copilot Studio or a comparable conversational agent platform.
• Ability to write code in C#, Python, or JavaScript and integrate REST APIs.
• Demonstrated ability to map business processes and identify worthwhile automation opportunities.
• Comfort working directly with non-technical stakeholders and translating their input into requirements.
• Clear written communication skills for documentation, runbooks, and training materials.

Nice To Haves

• Microsoft certifications such as PL-200, PL-400, PL-600, or AI-102.
• Experience with Azure AI Foundry, Azure OpenAI, or retrieval-augmented generation over internal content.
• Dataverse data modelling and Power Platform ALM across environments.
• Robotic process automation experience with Power Automate Desktop, UiPath, or Automation Anywhere.
• Experience automating back-office functions such as HR, finance, recruiting, or operations.
• Exposure to Power Platform governance, including DLP policies, environment strategy, and administration tooling.
• Prior experience working in a professional services or consulting firm.

Responsibilities

• Shadow internal teams to understand actual processes, including undocumented workarounds.
• Map current processes, including steps, handoffs, systems, time spent, and error points.
• Assess automation opportunities in terms of hours saved, errors avoided, or cycle time reduced.
• Recommend simplifying, consolidating, or eliminating processes when automation is not the right solution.
• Build conversational agents in Copilot Studio, including topics, knowledge sources, actions, and escalation paths.
• Build automations in Power Automate and applications in Power Apps using Dataverse or SharePoint as data layers.
• Integrate Microsoft 365, Teams, SharePoint, and internal line-of-business systems using connectors, APIs, or custom connectors.
• Write custom connectors, Azure Functions, scripts, and API integrations where low-code platforms are insufficient.
• Follow patterns, naming conventions, and environment standards set by the AI Solution Architect.
• Test solutions against real cases, including malformed inputs, exceptions, and edge cases.
• Train users and create usable documentation and runbooks.
• Track adoption and usage after launch, identify abandonment points and unanswered agent questions, and make improvements.
• Own fixes for delivered solutions after handover.
• Report automation outcomes in terms of hours returned or errors avoided rather than features delivered.
• Build reusable components, connectors, and prompt patterns, and contribute learnings to the internal pattern library.
• Flag governance and data-handling concerns, including access and information that should not reach a model.
• Evaluate new Microsoft platform capabilities and provide recommendations on whether to adopt them.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed