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.
• Proactively identify new automation opportunities across the organization.
• Run experiments and proof-of-concepts to validate new agent use cases before scaling.

What You Bring

• Proved experience in automation engineering, process automation, or a similar operational-technical role.
• Strong understanding of LLMs and context engineering: you know how to get consistent, reliable outputs from AI models in production contexts.
• Understanding and experience with APIs, MCP, skills-based agent architectures, and related integration standards.
• Process thinking ability to map a business process end-to-end, identify what can be automated, and design the right level of human oversight.
• Solid communication skills: you'll work with every department; you need to translate technical capabilities into business language and vice versa.
• Experience with agent frameworks (ADK, LangChain, LangGraph, CrewAI).
• Coding and development skills in Python.

Nice-to-Have

• Experience with additional enterprise automation platforms (Microsoft Power Automate, ServiceNow, or similar enterprise workflow tools).
• Familiarity with the broader Microsoft ecosystem (Power Platform, Azure AI Services, Azure AI Foundry)
• Experience with RAG (Retrieval-Augmented Generation) architectures and vector databases.