Senior Director, Head of Responsible AI Framework

Head of Responsible AI Framework

COGNIZANT OVERVIEW
Cognizant Technology Solutions (NASDAQ: CTSH) is one of the world’s leading professional services companies, transforming customers’ business, operating, and technology models for the digital economy. With annual revenues of $19.4 billion and a market value of $38 billion, we help global corporations adapt to market disruptions and build stronger, more agile, and innovative businesses.
At Cognizant, we give organizations the insights to anticipate what customers want and act instantly to deliver on those demands so our clients can achieve the goal of every modern business: staying one step ahead of a fast-changing world. In addition to honors such as being listed #194 on the 2022 Fortune 500, Cognizant was again named on Fortune’s List of the Global Most Admired Companies for 2022.
For more than 25 years, Cognizant has helped organizations across every industry envision, build and run more innovative and efficient businesses. And we’re just getting started.

COGNIZANT CULTURE
Our culture attracts those with a true passion for changing organizations for the better, desires to do so within a success-oriented, yet professional atmosphere filled with business professionals who all manifest a belief in partnership, innovation, and excellence. Our “Cultural Value Drivers” are well-known and clearly communicated within the organization: Open, Transparent, Driven, Empowered, Opportunity-Filled, Flexible & Collaborative.
Job Description:

Location: US
Reports To: Chief Responsible AI Officer
Job Type: Full-time

The Head of Responsible AI Framework is responsible for designing and managing the comprehensive Responsible AI (RAI) Framework that connects core principles to business outcomes through a structured implementation approach. This role orchestrates how responsible AI standards and governance requirements translate into practical implementation methodologies that deliver trusted, valuable AI solutions. The position focuses on creating a cohesive, scalable framework that bridges governance policies with technical execution while ensuring the framework adapts to evolving standards and technologies.

Key Responsibilities

1. Framework Architecture & Strategy
•Design the overall RAI Framework architecture that connects principles to outcomes.
•Establish the logical structure for how standards flow through implementation to deliver business value.
•Define how governance requirements translate into practical implementation approaches.
•Ensure the framework balances comprehensive governance with innovation enablement.
•Lead the continuous evolution of the framework to incorporate emerging practices and requirements.
•Build and lead a team of framework architects and implementation specialists to support adoption, integration, and scaling of the RAI Framework across the enterprise and client environments.

2. Framework Integration & Coherence
•Oversee seamless integration between different framework components and methodologies.
•Design the interconnections that create a coherent implementation approach.
•Ensure trust and governance mechanisms effectively connect principles to technical execution.
•Develop implementation methodologies that maintain consistency across diverse use cases.
•Establish the bridges between governance requirements and practical AI development practices.

3. Implementation Approach Development
•Develop practical approaches for operationalizing key Responsible AI principles, including:
•Translating transparency and explainability requirements into technical methodologies.
•Creating implementation approaches for fairness, privacy, and security controls.
•Establishing frameworks for risk assessment and compliance verification.
•Designing methodologies for model validation, testing, and continuous monitoring.
•Building coherent approaches for stakeholder engagement and education.

4. Cross-Functional Framework Leadership
•Work closely with the Governance Lead to ensure the framework effectively implements governance policies.
•Coordinate with the Product Lead to ensure technology platforms support the framework methodologies.
•Partner with Solution Architects to enable effective deployment in specific internal and client contexts.
•Collaborate with business leaders to ensure the framework supports strategic business objectives.
•Drive framework integration across the AI lifecycle, from development through deployment and evolution.

5. Framework Enablement & Evolution
•Develop comprehensive documentation and implementation resources.
•Create tools and methods that make the framework accessible and implementable across teams.
•Lead evangelism efforts to drive framework adoption within the organization and with clients.
•Establish feedback mechanisms to gather insights on framework effectiveness.
•Drive continuous improvement based on implementation experiences and emerging Responsible AI practices.

6. Requirement and Qualifications

Required Experience
•10+ years in developing complex enterprise frameworks, systems architectures, or governance infrastructures.
•5+ years in AI/ML solutions or platforms with exposure to governance, ethics, or responsible implementation.
•Proven success designing multi-layered frameworks that connect standards to operational and business outcomes.
•Experience working across business, technical, and governance domains to create cohesive systems.

Knowledge & Competencies
•Comprehensive understanding of AI/ML technologies, development lifecycles, and deployment environments.
•Deep knowledge of system design methodologies and framework architecture principles.
•Familiarity with AI governance frameworks and regulations (e.g., EU AI Act, NIST AI RMF, ISO 42001).
•Ability to translate high-level standards into implementable methodologies across technical and business domains.
•Strong systems thinking, communication, and cross-functional leadership capabilities.

Qualifications
•Advanced degree in Computer Science, Systems Engineering, Enterprise Architecture, or a related field.
•Experience developing AI or compliance frameworks in regulated industries such as finance, healthcare, or public sector.
•Certifications in architecture frameworks (e.g., TOGAF), AI governance standards, or risk methodologies.
•Experience with framework visualization, change management, and user adoption strategies.