Senior Agentic Insights Engineer - CA, Santa Clara, United States

Originally posted 17 September 2026 by the employer — open 1 day.

Develop and operate agentic infrastructure using the Model Context Protocol (MCP).

About the role

This role involves developing and operating agentic infrastructure to generate insights for IT leadership and the CIO. You will focus on delivering clear recommendations directly to IT leadership, replacing fragmented dashboards and static reports with a managed insights layer.

What you'll do

• Develop conversational analytics agents tailored to IT portfolio and program data.
• Link agents to enterprise data platforms via the Model Context Protocol (MCP) or equivalent open agent-tooling standards.
• Architect scheduled-push delivery mechanisms for persona-based insights in Slack and Microsoft Teams.
• Define and implement the agent-output validation layer to catch incorrect, ungrounded, or hallucinated results.
• Transform grounded agent output into clear operational recommendations, explaining what changed and the specific action to take.
• Manage the CIO executive insights digest and Planning & Portfolio Management reporting rhythm, linking "at risk" status to recommendations.

What you'll need

• 12+ years of experience in data/analytics engineering, BI development, or applied AI/ML engineering.
• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience.
• Hands-on experience building agentic AI workflows in production, including tool-calling, multi-step LLM orchestration, and MCP or equivalent integrations.
• Direct experience with a modern lakehouse platform (such as Databricks), including catalog-governed tables and conversational analytics tooling.
• Strong analytical judgment to validate or challenge AI-generated answers against underlying data.
• Demonstrated success in converting data into practical business or operational suggestions, not just dashboards.
• Experience building or integrating scheduled and event-driven delivery mechanisms into Slack, Microsoft Teams, or equivalent enterprise collaboration tools.
• Comfort operating as the primary technical builder on a small team, moving from prototype to production with a high degree of autonomy.