Data & AI Operations Manager

About the team

Zillow’s Legal & Compliance (L&C) Operations team empowers the department with innovative tools and resources, driving efficiency and effectiveness across Legal & Compliance. The team values new ideas and creative approaches, working collaboratively to deliver solutions that support Zillow’s mission.

About the role

As a Data & AI Operations Manager, you will own and drive how Legal & Compliance leverages data and automation. Your work will directly impact the speed, quality, and reliability of our processes, enabling teams to make better decisions and focus on high-value work. You will collaborate with stakeholders across Legal & Compliance, Operations, Data Engineering, and AI Engineering to prioritize opportunities, define success metrics, and deliver production-grade capabilities with measurable impact.

You Will Get To

• Lead stakeholders through process mapping and operational improvement, prioritizing opportunities for automation and analytics based on impact, risk, and feasibility

• Own the design, build, and iteration of low-code and AI-enabled workflows using tools such as n8n (a low-code automation platform), Zapier, and OpenAI Agent Builder.

• Translate business needs into reliable, production-grade automations, including exception handling and human-in-the-loop checkpoints.

• Develop and maintain evaluation sets, define quality thresholds, and run A/B tests to measure AI workflow performance.

• Integrate automation into dashboards and reporting, ensuring trusted, timely, and well-governed data is available to the right teams.

• Track and communicate the impact of automation and AI solutions on cycle time, accuracy, cost, efficiency, and risk turning results into insights and recommendations for senior stakeholders.

• Continuously assess new and existing applications and SaaS platforms to identify embedded or emerging AI capabilities.

• Lead pilots and proofs of value for new workflows or AI capabilities, defining success criteria upfront and incorporating stakeholder feedback into go-forward decisions.

• Provide training and enablement to Legal & Compliance teams, driving adoption and ongoing improvement.

• Partner with the Compliance Training team to create and incorporate AI use case specific policies and procedures into required learning programs.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.

In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $118,600.00 - $189,400.00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $112,700.00 - $179,900.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.

In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

Who you are

• 7+ years of experience in data operations, analytics, legal operations, or a related field, with hands-on experience designing, owning and scaling automated workflows.

• Proficient with low-code automation tools (e.g., Zapier, n8n) and integrating APIs and webhooks, with demonstrated ability to build reliable, supportable solutions.

• Experience working with AI platforms (e.g., ChatGPT Enterprise or similar large language models), including prompt design and evaluation.

• Familiarity with relational and semi-structured data models and the ability to translate data into decisions and prioritization; experience writing SQL and with data platforms such as Databricks is a plus.

• Experience with data integration tools (e.g., Airbyte), including handling schema changes and coordinating with data engineering.

• Familiarity with G