AI Engineer – Agentic Systems & Automation - Kennesaw, GA

United Contractor Services•Kennesaw, GA

5d•Onsite

About The Position

United Contractor Services is hiring a hands-on AI Engineer to build, deploy, and maintain production AI agents and automation across its operating companies. The engineer will turn business processes—including document intake, data extraction, system synchronization, internal copilots, decision support, and workflow orchestration—into reliable systems and remain accountable for their performance. The role reports directly to the Director of Technology. The position is full-time and in-office at the company’s headquarters in Kennesaw, Georgia. Remote and hybrid arrangements are unavailable, and relocation is not offered; candidates should be able to commute reliably from their first day. The engineer will design agentic systems using capabilities such as tool calling, multi-step reasoning, sub-agent orchestration, memory, retrieval, and human review. They will identify automation opportunities with business-unit leaders and operators, integrate agents with the company’s technology environment and external APIs, and implement secure identity, access, and audit patterns. They will also establish evaluation and observability pipelines, monitor reliability and performance, and maintain AI governance standards covering data handling, model selection, prompts, versioning, and rollback. Clear architectural documentation and practical recommendations on AI platforms are expected. The technology environment includes Microsoft 365, Entra ID, Intune, Azure Functions, Table Storage, Entra Domain Services, Procore, Make.com, and Microsoft Graph. Success will be measured by delivery speed, demonstrable business outcomes, reliability and cost efficiency, incident handling, and the maintainability, documentation, security, and knowledge-sharing of the systems delivered. Applicants should submit a brief description of an agentic AI system they have put into production, explaining its purpose, the hardest part of building it, how it was evaluated, and what they would change. Public repositories, write-ups, or recorded demos are welcome; a cover letter is not required. Candidates receiving an offer must undergo a drug test and background check in accordance with applicable laws.

Requirements

3 to 5 years of professional software engineering experience, including at least 1 year delivering AI/LLM systems in production.
Strong Python and/or TypeScript skills.
Hands-on experience with at least one major agent framework or SDK, such as Anthropic Claude SDK, OpenAI Agents SDK, LangGraph, Vercel AI SDK, Semantic Kernel, or Azure AI Foundry.
Experience building evaluation harnesses and interpreting results to determine whether an agent is working.
Working knowledge of Azure Functions, Microsoft Graph API, Entra ID app registrations, OAuth2, and managed identities.
Solid backend and integration skills, including REST APIs, webhooks, queues, state management, and authentication patterns.
Clear writing skills and ability to explain trade-offs to a technical leader making investment decisions.
Ability to work on-site daily in Kennesaw, Georgia.

Nice To Haves

Production experience with Microsoft Copilot Studio, Power Automate, or Azure AI Foundry.
Experience with Model Context Protocol (MCP) servers or similar tool-server designs.
Experience building retrieval-augmented generation (RAG) over enterprise document stores such as SharePoint, OneDrive, or Confluence.
Experience in multi-entity or multi-tenant environments where identity and data concerns span organizations.
Infrastructure-as-code or DevOps experience with Bicep, Terraform, GitHub Actions, or Azure DevOps.
Exposure to construction technology such as Procore or Bluebeam, or to vertical SaaS integrations.
Cybersecurity or compliance background, especially in AI governance, data classification, or zero-trust.
Open-source contributions to agent frameworks or developer tools.
Experience as one of the first AI hires at a company.

Responsibilities

Architect, build, and ship production agentic systems using tool calling, multi-step reasoning, sub-agent orchestration, memory, retrieval, and human-in-the-loop review.
Work with leadership and operators across business units to identify valuable automation opportunities and deliver agents to address them.
Integrate agents with Microsoft Graph, Entra, SharePoint, Teams, Procore, Azure Functions, Make.com, and external APIs.
Build secure agent identity and access patterns using managed identities, service principals, OAuth2 flows, least-privilege Graph permissions, and audit logging.
Establish evaluation pipelines and observability for production agents, covering cost, output quality, failure modes, and regression testing.
Monitor, troubleshoot, and improve agent performance as business needs and models change.
Set and maintain AI governance standards for data handling, model selection, prompt management, versioning, and rollback.
Document system architecture and technical decisions so systems can be maintained over time.
Track developments in agentic AI platforms and provide practical recommendations on platform selection.
Deliver maintainable code, documentation, security, and knowledge-sharing, and demonstrate business results from deployed systems.