Responsible AI, Lead Applied Scientist – X Delivery

Overview

In this role you will advance Responsible AI initiatives within BCG X, applying cutting-edge AI and GenAI to real-world problems. You will partner with AI product teams to design, test, and evaluate GenAI and AI products, ensuring safety, fairness, and accountability. You will help shape the Responsible AI program through independent risk assessments, experimentation design, and cross-functional collaboration. This position offers exposure to diverse use cases, industries, and clients with a focus on ethical innovation and responsible deployment.

Responsibilities

• Provide Responsible AI expert support to GenAI and AI product teams and conduct product-level risk assessments
• Collaborate with product teams across the software development lifecycle to support Responsible AI needs
• Contribute to risk assessment, testing, and evaluation of GenAI and AI products
• Train and mentor technical teams on testing and evaluation methods for GenAI products
• Stay current on emerging frameworks and standards through workshops, publications, and professional networks

Key requirements

• 3-5+ years of Responsible AI experience with engagement to AI product teams
• 3+ years of industry experience in building or evaluating Generative AI models
• Program/project management and team leadership experience
• Strong programming skills in Python and deep learning frameworks (PyTorch, TensorFlow)
• Knowledge of Responsible AI issues, regulatory frameworks, and best practices
• Excellent written and verbal communication across technical and non-technical audiences
• Ability to explain complex data science concepts to non-technical audiences and translate results into business implications
• Critical thinking about ethical, social, and business risks posed by GenAI and AI systems
• Experience designing and analyzing experiments using advanced statistical methods
• Experience with GenAI technologies

• communication of complex concepts
• leadership and mentorship
• collaboration across cross-functional teams
• Python
• PyTorch
• TensorFlow

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