Responsible AI Lead

Cayuse Holdings•Cedar Park, TX

1d•$80 - $100•Hybrid

About The Position

The Responsible AI Lead will establish and operationalize the organization’s approach to Responsible AI and AI governance across internally developed and third-party AI solutions. The role ensures AI systems are deployed ethically, effectively, and safely by designing and implementing frameworks, processes, and controls that support enterprise adoption and innovation. It will use proactive risk management and organizational alignment with ethical and regulatory standards to make Responsible AI a driver of business success. The position is based in Austin, Texas, follows a hybrid work model, and reports to the VP of Data & AI. It requires collaboration across multiple business units and regular on-site collaboration. The role develops and manages AI governance across the AI lifecycle, incorporates evolving laws and standards into organizational policies and controls, and embeds governance in operational processes. It also leads risk assessments and audits, provides leadership with visibility into the AI inventory and risk posture, and guides responsible AI adoption through standards, training, tools, and stakeholder communication. This is an independent contract position with an ASAP start date and a stated pay rate of $80–$100 per hour. The work involves frequent use of computer systems and virtual communication tools, and requires a professional demeanor when interacting within and outside the organization. The schedule may be adjusted and may include overtime and occasional weekend or evening hours.

Requirements

Proven experience designing and implementing Responsible AI or data/model governance frameworks.
Strong understanding of AI risks, including bias, transparency, privacy, model drift, and operational resilience.
Familiarity with legal and regulatory frameworks such as GDPR and the EU AI Act, and ability to translate them into actionable policies and controls.
Experience embedding governance practices into operational routines, such as SDLC and change management, for repeatable and scalable execution.
Ability to align cross-functional teams and manage complex initiatives.
Strong communication skills with technical and business audiences.
Deep familiarity with AI/ML technologies, risk management principles, and assessment methods.

Nice To Haves

Experience implementing governance or compliance programs in a highly regulated industry, such as finance or 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.

Responsibilities

Develop, implement, and manage an AI governance framework covering intake, design, build or buy, testing, deployment, monitoring, and retirement of AI solutions.
Monitor evolving laws, regulations, and standards, including the EU AI Act and GDPR, and incorporate them into internal policies, controls, and processes.
Define ownership, accountability, and decision-making processes for enterprise AI adoption.
Embed AI governance into operational processes such as SDLC, vendor management, model validation, privacy, and security reviews.
Lead AI risk assessments, audits, and impact analyses to identify, document, and mitigate ethical, regulatory, operational, and reputational risks.
Provide leadership with visibility into the AI inventory, risk posture, performance, operational stability, and remediation progress, along with actionable insights.
Collaborate with business, compliance, legal, IT, and other cross-functional teams to ensure AI solutions are responsibly designed, deployed, and monitored.
Evaluate AI use cases and vendor solutions, providing readiness evaluations and risk acceptance recommendations.
Promote responsible AI adoption by developing standards, guidelines, training programs, and practical governance tools.
Translate complex requirements into actionable frameworks and processes for consistent governance and risk management.
Align governance frameworks and initiatives with business strategies.
Communicate guidance to technical and non-technical stakeholders to support collaboration and decision-making.