Tech Stack

Description

You will embed responsible AI principles and controls across the AI development lifecycle, translate governance requirements into testable playbooks, and collaborate with cross-functional teams to ensure AI solutions are trustworthy and compliant.

Requirements

• 5+ years of hands-on experience in data and ML.
• Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, Statistics, or related quantitative field.
• Proven technical experience in regulated or complex industries.
• Track record of operationalizing responsible AI through technical development frameworks, testing protocols, and quantitative evaluation.
• Strong programming proficiency in Python, R, or similar languages, with experience in ML frameworks and responsible AI tooling.
• Understanding of AI and privacy regulations (EU AI Act, NIST AI RMF, GDPR, CCPA, ISO 42001).
• Exceptional communication skills.

Responsibilities

• Translate AI governance, regulatory, and compliance requirements into testable operational Responsible AI playbooks with quantifiable standards.
• Develop frameworks supporting systematic evaluation, testing, and risk mitigation.
• Build evaluation frameworks for data scientists and engineering teams.
• Develop testing principles for bias detection, model robustness, privacy preservation, and AI/privacy regulation alignment.
• Establish benchmarks and governance processes aligned with industry standards.
• Collaborate with data science and engineering teams to embed responsible AI controls.
• Develop repeatable testing and validation playbooks and evaluation frameworks.
• Pressure test AI solutions for accuracy, reliability, and trustworthiness.
• Develop methods to produce model cards and support audit trails.
• Act as internal subject matter expert on Responsible AI topics.
• Partner with Legal/Privacy/Risk, Technology, and D&A teams to translate regulatory requirements into controls.
• Collaborate on risk-informed design decisions.
• Establish Responsible AI frameworks and operational playbooks demonstrating alignment with regulations.
• Monitor emerging AI regulations and translate insights into internal guidance.