Job Description
Join NexusTech Solutions at the forefront of ethical AI development as we shape the responsible technology landscape of 2026. As our AI Ethics & Governance Lead, you'll architect frameworks ensuring AI systems align with human values while driving innovation. This role bridges cutting-edge technology with societal impact, requiring deep expertise in machine learning ethics, regulatory compliance, and stakeholder collaboration. You'll lead cross-functional teams to develop auditable AI governance models, conduct bias assessments, and pioneer transparency protocols that set industry standards.
We're seeking a visionary who thrives at the intersection of technology and philosophy, committed to building AI that augments humanity rather than replaces it. Our culture values intellectual curiosity, ethical rigor, and collaborative problem-solving. Enjoy competitive compensation, flexible work arrangements, and opportunities to speak at global AI ethics summits.
Responsibilities
- Design and implement AI ethics frameworks compliant with evolving regulations (EU AI Act, NIST AI RMF)
- Conduct algorithmic bias audits and mitigation strategies across ML pipelines
- Lead stakeholder dialogues with policymakers, NGOs, and industry coalitions
- Develop explainability protocols for high-stakes AI decision systems
- Create ethics training programs for engineering and product teams
- Establish continuous monitoring systems for AI system fairness and transparency
- Represent company at global AI ethics forums and thought leadership events
Qualifications
- PhD or Master's degree in AI Ethics, Philosophy, Computer Science, or related field
- 8+ years experience in AI governance, compliance, or responsible tech development
- Deep knowledge of global AI regulations and ethical frameworks
- Proven track record implementing bias detection tools in production systems
- Exceptional communication skills for translating technical ethics concepts
- Certification in AI Ethics (e.g., IEEE Ethically Aligned Design, EIT Digital)
- Experience with large-scale ML model deployment in regulated industries
- Published research on algorithmic fairness or AI transparency methods