AI Ethicist

At Macmillan Learning, we're committed to driving innovation that transforms education. We seek team members who thrive on pushing boundaries, envisioning future possibilities, and building solutions that make a lasting impact. Whether you're a Pioneer shaping bold new ideas, a Builder turning possibilities into reality, or a Stabilizer optimizing for success, you'll play a vital role in advancing our mission.

If you're excited by the prospect of testing new technologies, implementing transformative strategies, and thriving in a fast-paced, innovative environment, we'd love to hear from you!

The AI Ethicist / Responsible AI Specialist is a critical strategic role within Macmillan Learning's data and technology organization, responsible for ensuring that artificial intelligence systems-both those developed internally and those sourced from third-party providers-are designed, deployed, and governed in alignment with ethical principles, emerging regulatory requirements, and the educational mission of the company. This individual serves as the organization's primary authority on responsible AI, translating complex AI ethics concepts into actionable guidance for product teams, executives, customers, and institutional partners.

Reporting to the Chief Technology Officer, this role requires a practitioner who combines deep theoretical grounding in AI ethics, fairness, and accountability with sufficient technical fluency to engage credibly with data scientists, machine learning engineers, and senior AI researchers. The AI Ethicist is an active R&D collaborator and technology strategist-embedded with ML Engineering and Product teams to shape how AI is conceived and built-while also serving as a key partner to leading AI organizations such as Google, Anthropic, and OpenAI, and as a confident voice representing Macmillan Learning's responsible AI posture to customers, executives, and policymakers.

This role is eligible for a hybrid work schedule out of the Austin, TX office. It is expected that the incumbent will be based in Austin, TX.

We know that talented candidates sometimes hesitate to apply when they don't meet every single qualification listed. We encourage you to apply if you're excited about this role and believe you can contribute meaningfully to our team, even if your background doesn't align perfectly with every requirement. We're looking for people who are passionate about our mission and can bring valuable perspectives to our work.

Different experiences, skills, and approaches all have the potential to strengthen what we do. If this opportunity interests you, we'd love to hear how your unique background and abilities could contribute to our team's success. We're committed to building a workplace where everyone can do their best work and where diverse viewpoints are valued. We encourage all qualified candidates to apply - we're excited to learn about the different ways you might add value to our organization.

Major responsibilities include, but are not limited to:

AI Ethics Governance & Policy

* Develop, maintain, and operationalize Macmillan Learning's AI ethics framework and responsible AI policies.

* Define standards for fairness, transparency, accountability, and privacy across AI-driven products.

* Establish and chair an internal AI Review Committee to evaluate new AI capabilities prior to launch.

* Translate emerging regulatory requirements (e.g., EU AI Act, NIST AI RMF, state-level AI legislation) into actionable compliance roadmaps.

R&D Collaboration with ML Engineering & Product

* Serve as an embedded ethics and responsible AI partner within ML Engineering and Product R&D initiatives.

* Participate in model design reviews, feature conceptualization, and prototype evaluation to identify and resolve ethical risks early in the development process.

* Contribute to research into novel AI applications for learning-including adaptive systems, generative feedback, and intelligent assessment-ensuring that innovation is grounded in principled, well-documented methodology.

* Help define evaluation frameworks for experimental models that account for fairness, validity, and pedagogical soundness.

Product & Infrastructure Compliance Oversight

* Partner with Product, Technology, and Data Science teams during the AI development lifecycle to identify and mitigate ethical risks before deployment.

* Conduct algorithmic impact assessments and bias audits on existing and emerging AI models.

* Establish governance checkpoints within the MLOps pipeline and ensure documentation standards for model cards, data provenance, and audit trails are consistently met.

Internal Education & Culture Building

* Design and deliver responsible AI training programs for employees across Product, Engineering, Content, and Sales functions.

* Build internal resources and playbooks that embed ethical thinking into how teams work with AI tools and data.

* Act as an internal advisor and escalation point for teams encountering ambiguous AI ethics scenarios.

AI…