Cayuse Holdings

Responsible AI Lead

Cedar Park, Texas, US

Role snapshot

Cayuse Holdings is hiring a Responsible AI Lead on a full-time basis. This is a hybrid role based in Cedar Park, Texas, US.

Company: Cayuse Holdings
Location: Cedar Park, Texas, US
Work mode: Hybrid
Job type: Full-time
Posted: Nov 7, 2026

Who this role suits

The listing does not state a required experience level here. Read the requirements in the description below and apply if they match your background.

How to prepare your application

Match your résumé to the requirements in the description, using the same wording where it is honest to do so.
Prepare a short example for each requirement you meet, and be ready to explain any you only partly meet.
Read what Cayuse Holdings publishes about its product or team, so you can say clearly why this role and this company.

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About the role

Job Description

Overview

Job Title: Responsible AI Lead
Location: Auston, TX - Hybrid

Job Type: Independent Contract
Start Date: ASAP

Pay Rate: $80-100/hr

Job Summary

The Responsible AI Lead will establish and operationalize the organization's approach to Responsible AI and AI governance across both internally developed and third-party AI solutions. This leader will ensure AI systems are deployed ethically, effectively, and safely by designing and implementing frameworks, processes, and controls to support enterprise adoption and innovation. This role will transform Responsible AI into a driver of business success through proactive risk management and organizational alignment with ethical and regulatory standards.

This role reports to the VP of Data & AI and requires collaboration across multiple business units.

Responsibilities

Key ResponsibilitiesAI Governance and Risk Management

Develop, implement, and manage the AI governance framework across the entire AI lifecycle, encompassing intake, design, build/buy, testing, deployment, monitoring, and retirement of AI solutions.
Monitor and incorporate evolving laws, regulations, and standards (e.g., EU AI Act, GDPR) into internal policies, controls, and processes.
Define clear ownership, accountability, and decision-making processes for AI adoption across the enterprise.
Embed AI governance into existing operational processes, such as SDLC, vendor management, model validation, privacy, and security reviews, ensuring governance is part of daily activities.
Lead AI risk assessments, audits, and impact analyses to identify, document, and mitigate ethical, regulatory, operational, and reputational risks.
Provide comprehensive visibility into the organization's AI inventory, risk posture, performance, operational stability, and remediation progress, delivering actionable insights to leadership.
Collaborate with cross-functional teams (business, compliance, legal, IT, etc.) to ensure AI solutions are responsibly designed, deployed, and monitored.
Evaluate use cases and AI vendor solutions, offering readiness evaluations and risk acceptance recommendations.

Strategic Leadership and Operationalization

Promote responsible AI adoption by developing standards, guidelines, training programs, and practical tools to support governance implementation.
Translate complex requirements into actionable frameworks and processes to ensure consistent governance and risk management.
Align frameworks and initiatives with business strategies to transform Responsible AI into a competitive advantage.
Provide clear communication and guidance to technical and non-technical stakeholders for effective collaboration and decision-making.

Qualifications

Required Skills and Experience

AI Governance Expertise: Proven experience designing and implementing Responsible AI or data/model governance frameworks, with a strong understanding of risks such as bias, transparency, privacy, model drift, and operational resilience.
Regulatory Knowledge: Familiarity with legal and regulatory frameworks (e.g., GDPR, EU AI Act) and ability to translate them into actionable policies and controls.
Operational Fluency: Experience embedding governance practices into operational routines (e.g., SDLC and change management) for repeatable, scalable execution.
Leadership and Communication: Strong ability to align cross-functional teams, manage complex initiatives, and communicate effectively with technical and business audiences.
Technical Knowledge: Deep familiarity with AI/ML technologies, risk management principles, and assessment methods.

Preferred Qualifications

Experience implementing governance or compliance programs in a highly regulated industry (e.g., finance, healthcare).
Certifications or training in AI ethics, governance, or compliance.
Public thought leadership in Responsible AI.
Master’s degree in Data Science, Risk Management, or a related discipline.

Work Environment & Additional Information

Hybrid work model with regular on-site collaboration.
Flexibility for adjusted schedules, overtime, and occasional weekend/evening hours.
Frequent use of computer systems and virtual communication tools.
Professional demeanor required for interactions within and outside the organization.