AI & Automation Engineer

The AI & Automation Engineer is a hands-on technical role responsible for designing, building, deploying, and supporting AI agents, retrieval-augmented generation (RAG) capabilities, and automation solutions on Company-approved AI platforms. The position transforms prioritized use cases into secure, supportable production solutions, develops reusable patterns and knowledge layers, and serves as the primary technical builder for the Company's AI and automation programs under the direction of the Senior Manager of Infrastructure and AI. This position will require regular (every week) in-person attendance at one of our Foley Equipment offices with a partial week work-from-home opportunity. At this time, fully-remote is not available. Kansas City or Park City preferred. What You Will Do Solution Design and Development • Design, build, test, and deploy AI agents in Microsoft Copilot Studio and Foundry (topics, actions, tools, connected agents, knowledge sources) and publish them to approved channels such as Microsoft Teams. • Build the Power Platform components behind AI use cases: Power Automate flows, Dataverse data models and security roles, model-driven and canvas apps, AI Builder prompts, and Adaptive Card review experiences in Teams. • Integrate agents and flows with enterprise systems (ERP, CRM, data platform, Microsoft 365) using connectors, REST APIs, Microsoft Graph, Azure Functions, Logic Apps, and Model Context Protocol (MCP) tool connections. • Move prototypes into production through environment strategy, solution packaging and application lifecycle management (ALM), publishing, and release validation. Assist with evaluating the cost of proposed solutions. • Write supporting code (Python, PowerShell, C#, or JSON) where low-code tooling falls short and use AI-assisted development tools to accelerate delivery and legacy code modernization. AI Platform and Knowledge Engineering • Deploy and manage Azure AI Foundry projects, model deployments, and agents using Company-owned Azure Storage, Azure AI Search, and Cosmos DB so source data and vector indexes remain within the Company's tenant. • Build retrieval-augmented generation (RAG) pipelines (ingestion, chunking, embedding, indexing, vector and hybrid search) as reusable knowledge and context layers shared by multiple agents and automations. • Configure network isolation and identity for AI workloads, including private endpoints, private DNS, managed identities, and role-based access control (RBAC), and troubleshoot connectivity and authorization failures across platform boundaries. • Write system prompts and agent instructions, implements tool calling and orchestration, and run evaluations (test sets, groundedness and accuracy checks, regression tests) before and after each release. Security, Governance, and Responsible AI • Build every solution in accordance with Company security and data protection requirements, including least-privilege identities, scoped security roles, Entra ID app registrations, Power Platform data loss prevention (DLP) policies, sensitivity label requirements, and vendor and customer confidentiality obligations. • Verify each agent's authentication model, including end-user, maker, and agent-author credentials, to ensure the agent returns only information the requesting user is authorized to access. Apply content-safety controls, input and output validation, and human review for consequential actions. • Support the AI intake and review process with technical assessments, help identify and remediate unsanctioned AI usage, and support Microsoft 365 Copilot readiness, including permissions and oversharing remediation. Operations, Support, and Enablement • Monitor delivered solutions for accuracy, performance, usage, security, cost, and continued fit with the business need; track licensing, token, credit, and capacity consumption and recommended actions to control spend. • Provide third-tier support and root-cause analysis for production AI and automation solutions, including occasional after-hours work for urgent issues or production automation failures. • Maintain documentation for each solution (business owner, purpose, architecture, data sources, access model, prompts, testing notes, support owner, change history, retirement criteria) and follow Company change, release, and lifecycle practices. • Deliver demos and technical training on approved AI tools, mentor citizen developers and IT colleagues on approved patterns and review their work for security and supportability before production. • Communicate the status, risks, dependencies, and expected business value of assigned use cases to the Senior Manager of Infrastructure and AI and business stakeholders. Our Ideal Candidate • Strong understanding of generative AI, AI agents, retrieval-augmented generation, automation, low-code/no-code development, and practical business process improvement. • Hands-on experience with Microsoft's AI tech stack including Copilot Stu