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NVIDIA

Senior Agentic Insights Engineer

NVIDIA is hiring a Senior Agentic Insights Engineer in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include Databricks.
  • Level classifies it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Databricks

NVIDIA powers the AI revolution — and inside NVIDIA IT, we’re transforming how leadership makes decisions. Our AI Insights & Intelligence team is replacing fragmented dashboards and static reports with a managed insights layer. This layer delivers clear recommendations directly to IT leadership and the CIO.

We’re looking for a Senior Agentic Insights Engineer to be the hands-on technical builder behind this transformation. In this role, you’ll develop and operate the agentic infrastructure that generates insights. You will also apply your judgment to ensure every recommendation is accurate before it reaches a leader’s inbox. What makes this role outstanding? It blends production-level agentic AI engineering with direct responsibility for the operational recommendations that leadership implements within the same week. You’ll collaborate closely with our Planning & Portfolio Management and Enterprise Data Warehousing teams, using governed data to develop the insight and delivery layer on top. If you’re energized by building AI systems that compose real executive decisions — not just dashboards that sit on a shelf — this is your role.

What you’ll be doing:

  • Develop conversational analytics agents tailored to IT portfolio and program data. Link these agents to enterprise data platforms via the Model Context Protocol (MCP) or equivalent open agent-tooling standards for reliable data retrieval.

  • Architect scheduled-push delivery mechanics for persona-based insights in Slack and Microsoft Teams, demonstrating native platform capabilities where available and building custom integrations where they fall short.

  • Define and implement the agent-output validation layer. It catches incorrect, ungrounded, or hallucinated results before they reach leadership. This shifts the team’s reporting from manual dashboard authorship to agentic tooling.

  • Transform grounded agent output into clear operational recommendations. Explain what changed, why it matters, and the specific action a portfolio owner or executive should take. Deliver results in days, not sprint cycles.

  • Manage the CIO executive insights digest and Planning & Portfolio Management reporting rhythm, linking each “at risk” status to a specific recommendation instead of merely describing it.

  • Partner with Planning & Portfolio Management to keep aligned with their schedule, differentiating proposals that are feasible this week from those that should be assigned elsewhere.

  • Apply data storytelling and UX expertise to frame each insight for its specific audience, ensuring leadership can act on it within minutes.

  • Collaborate with the Enterprise Data Warehousing, AI Engineering, and Reporting & Dashboards teams to ensure uniformity in metric definitions, data certification, and delivery throughout the organization.

What we need to see:

  • 12+ years of experience in data/analytics engineering, BI development, or applied AI/ML engineering, with a 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 is required. This includes tool-calling, multi-step LLM orchestration, and MCP or equivalent experience integrations. You should understand failure modes like hallucinated tool calls, runaway loops, and non-deterministic output.

  • Direct experience with a modern lakehouse platform (such as Databricks), including catalog-governed tables and conversational analytics tooling.

  • Strong analytical judgment demonstrated by the ability to validate or challenge AI-generated answers against underlying data before they ship to a business audience.

  • Demonstrated success in converting data into practical business or operational suggestions instead of only dashboards. Skilled at writing for a CIO or VP audience, ensuring the message is clear in under three minutes.

  • 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.

Ways to stand out from the crowd:

  • Experience replacing a manual or contractor-dependent BI/reporting function with an agentic or automated alternative.

  • Familiarity with enterprise program and portfolio management tools like Jira-based platforms is required. The role involves building automated, executive-facing reports with push/pull and agentic delivery methods.

  • Applied use of prescriptive analytics techniques — trend detection, anomaly flagging, or forecasting — in service of operational decision-making.

  • Prior partnership with C-level or VP-level collaborators on recurring executive reporting.

  • Contributions to an internal agent or skills community of practice, or experience building reusable agent capabilities for others to extend.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 184,000 USD – 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 6, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Senior Agentic Insights Engineer at NVIDIA rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Databricks

Questions you could be asked

  1. What's a project where you used Databricks hands-on?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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