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Information Technology 🏢 Full Time ⭐️ Verified

AI Ethics & Governance Lead

Nexus Future Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of shaping humanity's technological future. As our AI Ethics & Governance Lead, you'll architect responsible AI frameworks for systems that will define 2026 and beyond. We're seeking visionary pioneers to build ethical guardrails for autonomous systems, ensuring alignment with human values while driving innovation. Work with Fortune 500 partners to implement auditable AI governance protocols and lead cross-functional teams in developing next-generation compliance frameworks. This is your opportunity to influence how artificial intelligence evolves in the critical decade ahead.

Responsibilities

  • Design and implement AI ethics governance frameworks for enterprise-scale autonomous systems
  • Lead cross-functional audits of algorithmic bias and fairness in predictive models
  • Develop compliance protocols for emerging AI regulations (EU AI Act, US AI Bill of Rights)
  • Partner with product teams to embed ethical-by-design principles in AI development lifecycles
  • Establish transparency mechanisms for explainable AI (XAI) implementations
  • Create stakeholder communication strategies for AI risk disclosure
  • Lead incident response protocols for AI system failures

Qualifications

  • Master's degree in Computer Science, AI Ethics, Philosophy, or related field
  • 5+ years in AI governance, ML ethics, or responsible AI implementation
  • Expertise in regulatory frameworks (GDPR, NIST AI RMF, ISO/IEC 42001)
  • Experience with bias detection tools (IBM AI Fairness 360, Google What-If Tool)
  • Published work on algorithmic accountability or AI ethics
  • Strong background in cross-functional stakeholder management
  • Certification in AI governance (e.g., CEGAI, AIGP) preferred

Required Skills

AI Ethics Machine Learning Governance Regulatory Compliance Algorithmic Bias Explainable AI Risk Management Stakeholder Communication

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