Chief Responsible AI Architect

1 week ago

Bareilly, Uttar Pradesh, India beBeeFairness Full time ₹ 25,00,000 - ₹ 45,00,000
Responsible AI Professional

We are seeking an accomplished expert in responsible AI development to join our organization.

As a key member of our team, you will play a crucial role in assessing, auditing, and ensuring the ethical deployment of AI systems across our enterprise.

This position involves evaluating traditional ML models, Large Language Models (LLMs), and Generative AI systems, focusing on fairness, transparency, privacy, security, and accountability across multi-cloud environments.

The ideal candidate combines deep technical expertise with a firm grasp of ethical frameworks, regulatory requirements, and responsible AI principles.

  • Evaluate AI/ML, LLM, and GenAI models for bias, fairness, explainability, and robustness.
  • Conduct red-teaming, safety testing, and adversarial analysis across AI pipelines.
  • Perform pre-deployment, post-deployment, and continuous model audits.
  • Implement responsible AI frameworks based on NIST AI RMF, OECD, ISO/IEC 42001, and industry standards.
  • Collaborate with data scientists, legal, compliance, and product teams to enforce responsible AI lifecycle checkpoints.
  • Ensure AI/ML systems meet data residency, compliance, and ethical standards across AWS, Azure, GCP, and hybrid environments.
  • Build or integrate tools for model explainability, fairness, and privacy.

Required Skills and Qualifications

  • 5+ years of experience in AI/ML evaluation, testing, or assurance roles.
  • Proven experience with LLMs and generative AI.
  • Strong knowledge of fairness, bias detection, differential privacy, red-teaming, model transparency techniques.
  • Familiarity with AI regulation and governance.
  • Experience with cloud platforms and deploying/evaluating AI services in distributed architectures.
  • Proficiency in Python and relevant libraries.

Desirable Qualifications

  • Master's or PhD in Computer Science, Data Science, Ethics, or related field.
  • Prior work with model evaluation benchmarks and large-scale LLM testing frameworks.
  • Knowledge of secure and privacy-preserving ML techniques.

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