Support Engineer – AI & Automation

What happens when an AI or automation solution is already in production—but something goes wrong? We're looking for a **Support Engineer – AI & Automation** to help keep ATI's AI, LLM, and RPA solutions running reliably in production. This role sits at the intersection of technology, automation, and operations, supporting everything from robotic workflows and transaction queues to LLM and RAG pipelines. You'll monitor production environments, investigate incidents, troubleshoot automation and AI workloads, and work closely with Service Desk, AI/RPA Engineering, and technology partners to get issues resolved quickly and effectively. If you enjoy troubleshooting complex technical problems, working with emerging AI technologies, and making sure production systems perform as they should, this could be your next challenge. ### Key Responsibilities - Monitor and maintain the operational health of **AI, LLM, and RPA solutions** running in production - Manage RPA queues, transactions, robots, triggers, assets, and other **UiPath Orchestrator** components - Troubleshoot and resolve incidents across RPA workflows, AI applications, LLM services, and supporting infrastructure - Support **LLM and RAG pipelines**, including investigating model responses, API issues, retrieval problems, and common LLM failure modes - Monitor application, automation, and model performance using appropriate observability and monitoring tools - Distinguish between **business exceptions and application exceptions** and apply the appropriate resolution or escalation path - Maintain and improve incident runbooks, troubleshooting guides, and operational documentation - Support prompt, model, and configuration changes while ensuring appropriate controls and testing are followed - Support change and release activities for RPA bots, AI applications, and related components - Conduct post-incident reviews to identify root causes and opportunities to prevent recurring issues - Collaborate with AI/RPA Engineering, Service Desk, Cloud, and business teams to resolve incidents and improve production reliability - Work with technology vendors and platform providers when issues require external investigation or escalation - Continuously identify opportunities to improve monitoring, automation support processes, and overall platform reliability ### Is this you? - Bachelor's degree in **Computer Science, Information Technology, Software Engineering, Information Systems, or a related technical field** - **3+ years of experience** in technical support, RPA operations, DevOps, ML engineering, or a similar production technology role - Demonstrated experience supporting **UiPath RPA solutions and/or LLM workloads in production environments** - Strong hands-on knowledge of **UiPath Studio and Orchestrator**, including attended and unattended robots, queues, assets, triggers, and folders - Experience with **UiPath REFramework** or equivalent automation framework patterns, such as dispatcher/performer architectures - Working knowledge of [****](http://VB.NET) **or C#** for UiPath scripting, troubleshooting, and debugging - Intermediate **Python** skills for scripting, debugging, and data processing - Experience working with **LLM APIs**, such as OpenAI, Azure OpenAI, Anthropic, Cohere, or similar platforms - Experience with IT Service Management tools such as **Jira Service Management, ServiceNow**, or equivalent - Understanding of at least one major cloud platform: **Microsoft Azure, AWS, or Google Cloud** - Working knowledge of **SQL and data querying** for investigating application logs, transaction data, and automation platform data - Experience creating, maintaining, or following **incident runbooks and troubleshooting procedures** - Understanding of automation exception handling, including the ability to distinguish **business exceptions from application exceptions** - Understanding of **RAG architecture** and common LLM failure modes - Experience with **UiPath AI Center, Document Understanding, or Communications Mining** - Exposure to **Microsoft Power Automate** as a secondary RPA platform - Experience with vector databases such as **Azure AI Search, Pinecone, or Weaviate** - Experience with AI orchestration frameworks such as **LangChain, LlamaIndex, or Semantic Kernel** - Exposure to observability and monitoring tools such as **Grafana, Azure Monitor, Datadog, LangSmith, or Weights & Biases** - Experience with **CI/CD pipelines**, including Azure DevOps or GitHub Actions, for bot packages and AI applications - Familiarity with model evaluation concepts such as **BLEU, ROUGE, human evaluation, or LLM-as-judge** - Exposure to **MLflow, Kubeflow**, or similar ML lifecycle platforms - Experience with prompt engineering, evaluation-driven workflows, or model optimization - Understanding of data privacy, AI governance, and RPA controls, including **PII handling and automation controls**