RAI Lead

RWE•Austin, TX

18h•Onsite

About The Position

The AI Transformation team, part of the broader Strategy department, leads the company's AI agenda from ambition setting through blueprinting (designing AI-enabled workflows) and execution. The team partners with the Executive Leadership Team (ELT) to define AI priorities and works closely with IT and business functions to deliver against the strategy. It also monitors the evolving AI landscape, translating emerging trends into actionable opportunities in collaboration with relevant business units.

Requirements

Master’s or Ph.D. in Computer Science, Data Science, Ethics, Law, or a related field, with a focus on AI/ML, ethics, or governance
Minimum 11 years of relevant professional experience in responsible AI, technology governance, regulatory compliance, ethics, or related roles
Deep expertise in responsible RAI best practice, frameworks, and the AI regulatory landscape, with the ability to translate complex requirements into practical, enforceable controls
Superior, structured problem-solving ability, navigating highly ambiguous challenges at the intersection of technology, law, ethics, and business needs to deliver clear policy recommendations
Outstanding written and verbal communication skills, including experience preparing materials for C-suite and board-level audiences on governance risk and strategic RAI positioning
Highly skilled at engaging and influencing senior stakeholders, building consensus across cross functional stakeholders on RAI standards
Consistent commitment to excellence and innovation, identifying and embedding emerging best practices in responsible AI as the regulatory and technical landscape evolves
Courage and decisiveness, willing to challenge AI product and delivery teams where ethical or regulatory controls are insufficient, and maintain those positions under pressure
Experience in the power, utilities, or clean energy sector, including knowledge of U.S. power markets, renewable project development, and clean energy technologies preferred
Solid understanding of AI product development processes, including model lifecycle management, stage-gate governance, and deployment practices, sufficient to evaluate RAI compliance at each stage and engage credibly with technical teams and product squads
Applicants must be legally authorized to work in the United States. RWE Americas is unable to sponsor or take over sponsorship of employment visas at this time.

Nice To Haves

Certifications or specialized training in Responsible AI, AI ethics, or governance frameworks are preferred

Responsibilities

Own the enterprise Responsible AI framework, embedding legal, regulatory, and ethical controls including risk classification / assessments throughout the lifecycle of AI products
Serve as the company's RAI expert and strategic advisor to the ELT, leading the RAI working team - a governance committee that reports to the AI SteerCo (including the CEO) - to oversee portfolio-level risk and drive consistency of responsible AI application across the enterprise
Shape the organization's position on RAI standards while engaging with internal and external stakeholders
Maintain and operationalize the RAI handbook in partnership with legal, IT/OT, and other stakeholders, ensuring controls are practical, enforceable, and aligned with evolving regulatory requirements
Embed RAI controls, risk scoring, and ongoing monitoring directly into the product lifecycle and stage gates, ensuring ethical and regulatory requirements are tested and validated at each stage of delivery, and that remediation processes are in place when issues are identified
Review and approve RAI assessments for AI products and manage third-party vendor compliance across the portfolio, evaluating risk across established ethical AI principles
Track and report AI-related incidents to the ELT, maintaining a structured incident log, assessing risk implications, and ensuring timely escalation, remediation, and closure in line with the enterprise RAI framework
Drive RAI awareness and capability-building across the organization, design training / guidance materials and engagement programs that embed responsible AI thinking into squad-level delivery