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AI Ethics Specialist (2026 Vision)

Nexus Solutions
Austin
Estimated Salary
USD 120.000 – USD 180.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Solutions at the forefront of responsible AI development as we pioneer ethical frameworks for the 2026 technological landscape. We're seeking an AI Ethics Specialist to shape the future of human-AI collaboration in our state-of-the-art Austin R&D hub. This role bridges cutting-edge AI innovation with robust ethical governance, ensuring our autonomous systems align with societal values while maintaining competitive advantage. You'll work directly with C-suite executives, research scientists, and product teams to embed ethical principles into AI lifecycles from conception to deployment.

Responsibilities

  • Develop and implement comprehensive AI ethics frameworks aligned with 2026 regulatory requirements
  • Conduct bias audits and fairness assessments across machine learning models
  • Lead stakeholder workshops to establish ethical AI governance protocols
  • Author whitepapers on emerging ethical challenges in autonomous systems
  • Collaborate with engineering teams to embed ethical safeguards in AI pipelines
  • Monitor global AI regulatory trends and advise on compliance strategies
  • Establish KPIs for ethical AI performance and track implementation metrics

Qualifications

  • Master's degree in Ethics, Philosophy, Computer Science, or related field
  • 3+ years of experience in AI governance or responsible tech development
  • Deep understanding of EU AI Act, NIST AI RMF, and evolving ethical standards
  • Proficiency in Python for bias detection and fairness analysis tools
  • Exceptional communication skills for translating technical concepts to non-technical audiences
  • Published research or practical experience in algorithmic accountability
  • Certification in AI ethics or responsible AI (e.g., from IEEE or Partnership on AI)

Required Skills

AI Ethics Machine Learning Governance Regulatory Compliance Python Stakeholder Management Algorithmic Fairness Risk Assessment

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