AI Operations & Adoption Analyst

Ken Garff Automotive Group•Salt Lake City, UT

2d•Hybrid

About The Position

Ken Garff Automotive Group is building a brand new AI team and looking for an AI Operations & Adoption Analyst to serve as the connective tissue between our data science capabilities, our business teams, and our AI platform. This is not a deeply technical engineering role - it is a role for someone who is technically fluent, operationally sharp, and genuinely energized by getting people and systems working together. The AI Operations & Adoption Analyst will own the day to day operation and governance of our AI platform, translate business needs into platform configurations, validate that automated decisions and agent outputs are working as intended, and drive adoption across the organization. Much of this work centers on agentic systems - designing, deploying, and governing AI agents that take actions on behalf of the business so candidates with hands-on experience configuring or operating agentic platforms will be especially relevant. This person sits at the center of everything the team builds, making sure it lands, sticks, and delivers real value to the business. The ideal candidate combines solid data literacy with strong communication and organizational skills, a bias toward action, and the curiosity to figure things out in an environment that is still finding its footing. Comfort with ambiguity is essential. This is early stage platform work, and it rewards people who poke at things and solve problems.

Requirements

Solid data literacy - comfortable with SQL, BI tools, and interpreting analytical outputs even without building them from scratch.
Prompt fluency - able to write clear, effective instructions for AI agents and evaluate whether their outputs are correct, hallucinated, or drifting.
Process mapping - able to document how workflows actually run today and translate them into structured configurations.
Stakeholder management - proven ability to build relationships across functions, manage expectations, and communicate complex things simply.
Conceptual understanding of integrations and APIs - knows what connects to what and can have an informed conversation without needing to build it.
Change management and training - experience developing training materials and driving adoption of new tools or processes.
Comfort with ambiguity - thrives in early-stage environments where the answer isn’t always clear and the process is still being built.
Attention to detail - especially around data validation, output quality, and documentation.
Bachelor’s degree in Business, Information Systems, Data Analytics, or a related field.
2–4 years in a role that required hands on configuration and administration of a business platform - examples include Salesforce admin, ServiceNow admin, HubSpot ops, BI platform admin, RPA/workflow tool admin, or similar - or equivalent experience in business analysis, analytics operations, or data governance.
Comfortable querying data with SQL - doesn't need to be an expert but can write a join and interpret results.
Experience translating business requirements into operational or technical configurations.
Experience working cross-functionally with both technical and non-technical stakeholders.

Nice To Haves

Familiarity with Snowflake, BI tools (Tableau, Power BI, or similar), and modern analytics environments preferred.
Experience developing and delivering training or documentation for non-technical audiences preferred.
Experience with AI platforms, prompt engineering, or automated decision systems.
Hands-on experience with agentic AI systems — deploying agents, designing agent workflows, writing and governing agent instructions, or operating an agentic platform — strongly preferred.

Responsibilities

Serve as the primary administrator for the AI platform, configuring decision policies, governance rules, and agent instructions.
QA and validate automated decisions and agent outputs before they go live - catching errors, hallucinations, or drift before they reach the business.
Tune and iterate on the prompts and instructions that drive AI agents, evaluating outputs and improving them based on results.
Monitor platform performance and governance data month over month, surfacing trends and anomalies to the team.
Maintain documentation of platform configurations, workflows, and governance standards.
Map and document how business workflows actually operate across departments - translating real-world processes into platform configurations.
Translate business requirements (“the F&I team needs X”) into actionable platform configuration and governance rules.
Drive user adoption across 70+ locations by developing training materials, leading onboarding sessions, and building internal capability.
Serve as the primary liaison between the data science team, business stakeholders, and our external platform partner.
Manage stakeholder relationships across service, sales, parts, and sister company teams, ensuring the team’s work is understood and trusted.
Support change management efforts as new AI enabled capabilities are rolled out across the organization.
Use SQL and BI tools to query data, build dashboards, and interpret what the semantic layer is producing.
Validate data definitions and metric consistency across locations, flagging discrepancies to the data scientist.
Support the data science team with exploratory analysis, reporting, and data quality validation as needed.
Develop a working understanding of integrations and APIs - knowing what connects to what, even without building it.