# Senior AI Automation Manager, Business Intelligence

**Company:** [DAT Freight & Analytics](https://hotfix.jobs/companies/dat-freight-analytics)
**Location:** Seattle, WA
**Role:** Data Analytics
**Salary:** $141k – $190k/yr
**Experience:** 3+ years
**Skills:** Business Intelligence, Data Analytics, Kpi Development, Dashboard Development, Data Modeling, AI Agents, Llm Tools, Prompt Engineering, Data Quality, Stakeholder Management
**Posted:** 2026-05-19

> Senior AI Automation Manager who builds and owns KPIs, delivers strategic analytics, and designs/deploy AI agents to automate BI workflows for leadership decision-making.

## Job Description

## What You’ll Do

- **KPI development & ownership**: Develop and own the key performance indicators that leadership uses to measure business health, ensuring metrics stay aligned with evolving strategic priorities.
- **Strategic & ad-hoc analysis**: Partner with stakeholders across Operations, Finance, Product, and Marketing to scope analytical questions, deliver deep-dive insights, and translate findings into clear recommendations that drive business decisions.
- **BI development & reporting**: Build and maintain dashboards, reports, and data models that make key business metrics accessible, accurate, and trustworthy across the organization.
- **Agent design & deployment**: Design, prototype, and deploy AI agents that augment BI workflows, including agents that monitor metrics for anomalies, generate narrative summaries, answer ad-hoc data questions, and automate routine reporting cycles.
- **Performance monitoring & iteration**: Track how deployed agents and dashboards perform in the wild, gather feedback from end users, and continuously refine outputs to improve accuracy, usefulness, and adoption over time.
- **Automation opportunity identification**: Spot repetitive analytical tasks across the organization and evaluate which are best suited for agentic automation versus traditional BI tooling, balancing impact, complexity, and risk.
- **Data quality & integrity**: Partner with Data Engineering to validate source data, surface inconsistencies, and ensure that both human-facing analyses and agent outputs are built on a trustworthy foundation.
- **Documentation & enablement**: Document agent capabilities, limitations, and intended use cases so stakeholders know when to trust outputs and when to escalate or verify.

## The Skills and Experience You’ll Bring

- 3–8 years in a business intelligence, data analytics, or analytical consulting role with a track record of turning data into decisions.
- Demonstrated ability to translate ambiguous business questions into structured analyses and clear recommendations.
- Fluency with AI tools in your day-to-day work; comfortable writing clear prompts, evaluating outputs, debugging agent behavior, and knowing when human judgment must override automation.
- Ability to distill analytical work into digestible presentations and communicate learnings clearly.
- Growth mindset and a willingness to work hard – this will be a high-effort, high-reward type role for those excited about building business leverage with AI.

## Nice to Haves

- Experience deploying AI agents or LLM-powered tools, including thinking through evaluation, monitoring, and failure modes.
- Experience in fintech, payments, banking, or logistics.

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