Job Description & Details
This role sits at the intersection of enterprise SaaS administration and emerging AI tooling, meaning you will spend your days bridging the gap between cutting-edge LLMs and secure internal business workflows. If you enjoy wrangling APIs, figuring out why an agent integration dropped its authentication token, and helping teams safely adopt generative AI without leaking company data, this position is worth a serious look.
What You'll Actually Be Doing
You'll spend your time supporting, configuring, and scaling AI ecosystems across the enterprise. Your day-to-day involves troubleshooting integration failures between LLMs and internal data sources, managing user access controls, and building out automation scripts to streamline how teams interact with tools like Copilot, ChatGPT Enterprise, or Vertex AI. Expect to handle incidents related to API rate limits, RAG grounding issues, and permission mismatches while collaborating with security teams to ensure compliance.
The Core Tech Stack
You need a solid foundation in cloud administration, identity and access management (IAM), and REST APIs. Familiarity with Microsoft Entra ID or Google Identity is critical for handling service accounts and RBAC policies. On the AI side, practical exposure to OpenAI APIs, Azure AI, or Google Gemini is non-negotiable, alongside enough Python or PowerShell scripting to automate repetitive support operations and parse JSON payloads.
Interview Expectations
Expect the hiring manager to ask you to trace the lifecycle of a failed RAG query, specifically how you would troubleshoot a scenario where an AI agent hallucinates due to poor knowledge grounding or returns a 403 error due to an IAM misconfiguration. They want to see how you systematically debug asynchronous API calls and enforce data-loss prevention guardrails without completely breaking developer velocity.
Application Advice
To get past the ATS, make sure your resume explicitly highlights your hands-on work with major AI ecosystems alongside traditional cloud or SaaS administration. Instead of just listing tools, weave in specific examples of how you have managed API integrations, automated workflows with Python or PowerShell, and enforced security compliance or access controls in previous engineering roles.