AI Operations Engineer

About the role

About CoreView

CoreView is the global leader in Microsoft 365 (M365) tenant resilience, serving over 23 million users worldwide. We empower the world’s leading organizations to master the complexity of Microsoft M365. Through robust security and precise governance, we help ensure that our client’s environments stay cyber-resilient and productive, no matter how complex they are.

Our unified, cloud-native platform delivers powerful automation, rapid value, and end-to-end visibility across the entire M365 ecosystem. Backed by world-class support and a collaborative, innovative culture, CoreView is a place where your ideas matter, and your work truly impacts global enterprises.

We're looking for an AI Operations Engineer to join the AI Operations team, and help design, build, and maintain AI-powered agents and automated workflows that streamline internal operations across CoreView, from Support and Finance to HR, Sales Operations, and Product.

This is not a traditional software engineering role. You'll work at the intersection of business processes, automation, and AI, translating operational bottlenecks into reliable autonomous or semi-autonomous agents that handle transactional, repetitive, and data-intensive work.

What You'll Do

Agent Design & Development

- Design, build, deploy, and iterate on internal AI agents and solutions using enterprise-grade agentic workflow platforms.

- Implement agents across multiple business functions, including but not limited to: Support, Finance & Accounting, Business Intelligence, HR, Marketing & Content, Product, and Sales & Revenue Operations.

- Define agent behaviors, guardrails, escalation paths, and human-in-the-loop checkpoints.

- Analyze internal data sources across departments, identify high-value data, and extract the insights each team needs to feed and optimize their agents.

Platform & Infrastructure

- Evaluate, select, and own the company's agentic workflow platform(s), establishing the technical foundation for secure, scalable, and governed internal AI automation.

- Integrate agents with existing tools and systems (CRM, ticketing systems, ERP, data warehouses, communication platforms, etc.) via APIs, MCPs, webhooks, and native connectors.

- Manage context engineering, LLM selection, model configuration and agent evaluation for each agent use case.

- Ensure data security, access control, and compliance across all automated workflows.

Enablement & Governance

- Create templates, playbooks, and documentation so domain experts in each department can propose, configure, or co-build agents relevant to their function.

- Establish governance frameworks: monitoring, logging, quality assurance, and performance tracking for all deployed agents.

Continuous Improvement

- Stay current on the rapidly evolving AI/agent landscape: new models, frameworks, platforms, and best practices.