Responsible AI Expert

2 days ago

Palakkad, Kerala, India beBeeAI Full time ₹ 15,00,000 - ₹ 20,00,000

About Our Role:

We are seeking a highly skilled and principled professional to evaluate, audit, and ensure the ethical development and deployment of AI models across our enterprise.

This role spans traditional ML models, Large Language Models (LLMs), and Generative AI systems, with a strong focus 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.

Key Responsibilities:

  • 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.
  • Operationalize and implement RAI principles based on NIST AI RMF, OECD, ISO/IEC 42001, and industry standards.

We will collaborate with data scientists, legal, compliance, and product teams to enforce responsible AI lifecycle checkpoints.

This role also includes ensuring AI/ML systems deployed across AWS, Azure, GCP, and hybrid environments meet data residency, compliance, and ethical standards.

The individual will build or integrate tools for model explainability, fairness, and privacy, leveraging LLM-specific eval frameworks, and produce model cards, system cards, and impact assessments.

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.

PREFERRED 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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