Job Description
Join Nexus Horizons at the forefront of ethical AI innovation as we shape responsible technology for 2026. We're seeking a visionary AI Ethics Strategist to design frameworks that ensure our autonomous systems align with human values. This role bridges cutting-edge AI development with societal impact, requiring a blend of technical expertise and philosophical rigor. You'll collaborate with quantum computing researchers, neuroscientists, and policy architects to create governance protocols that set industry standards for the next decade. Our dynamic team operates at the intersection of ethics and exponential technology, offering unparalleled opportunities to influence how humanity co-evolves with artificial intelligence.
Responsibilities
- Design and implement ethical AI governance frameworks for autonomous systems and neural networks
- Conduct bias audits and impact assessments on machine learning models using quantum verification tools
- Develop stakeholder engagement protocols for diverse communities affected by AI deployments
- Lead cross-functional workshops with robotics engineers and bioethicists to align technical solutions with human-centric values
- Author position papers and policy recommendations for global AI regulatory bodies
- Monitor emerging ethical challenges in generative AI and neuromorphic computing
- Establish KPIs for ethical AI performance across enterprise systems
Qualifications
- PhD in Ethics, Philosophy, Computer Science, or related field with 5+ years applied AI ethics experience
- Expertise in bias mitigation techniques for large-scale neural networks and federated learning systems
- Proven track record of developing AI governance frameworks adopted by Fortune 500 companies
- Deep understanding of ISO/IEC 42071 and EU AI Act compliance requirements
- Published research on algorithmic fairness or explainable AI in peer-reviewed journals
- Experience with participatory design methodologies for ethical technology development
- Proficiency in Python for ethical auditing and simulation modeling