Job Description
Join Quantum Leap Innovations as our pioneering 2026 AI Ethics Lead and shape the future of responsible artificial intelligence. We're seeking a visionary leader to develop ethical frameworks for our next-generation AI systems, ensuring alignment with human values while driving technological breakthroughs. This role offers unparalleled impact at the intersection of innovation and ethics, with opportunities to influence global standards.
Our Austin-based team operates at the forefront of emerging technologies, offering competitive benefits, flexible work arrangements, and a culture that values both cutting-edge solutions and moral integrity. If you're passionate about ensuring AI serves humanity responsibly, this is your moment to lead.
Responsibilities
- Design and implement comprehensive AI ethics governance frameworks for 2026-era autonomous systems
- Lead cross-functional audits of AI models using bias detection and fairness assessment tools
- Develop predictive protocols for emerging ethical challenges in quantum computing integration
- Collaborate with product teams to embed ethical-by-design principles into development lifecycles
- Represent the company at global AI ethics summits and regulatory consultations
- Mentor junior researchers on responsible AI practices and moral reasoning frameworks
- Produce annual ethics impact reports for stakeholders and regulatory bodies
Qualifications
- PhD in Computer Science, Philosophy, Ethics, or related field with 5+ years AI ethics experience
- Proven expertise in bias mitigation techniques for large-scale neural networks
- Published research on AI alignment or moral machine learning frameworks
- Experience navigating regulatory landscapes (EU AI Act, NIST AI RMF)
- Strong background in quantum computing ethics or post-quantum cryptography
- Exceptional communication skills for translating complex ethical concepts
- Portfolio demonstrating ethical AI implementations in production environments
- Certification in Responsible AI (e.g., IBM AI Ethics, Google ML Fairness)