SVP, Chief AI Officer

Rackspace; City Of London; On-site; GBP 150,000 - 200,000; Full time

Job summary

A leading multicloud solutions provider is seeking a Senior Vice President, Chief AI Officer to define and execute AI strategies that drive business impact. This executive will establish governance frameworks, optimize AI adoption, and collaborate with various teams to integrate AI into products and services. Candidates should possess deep expertise in AI technologies and significant leadership experience, with an advanced degree preferred.

Qualifications

• Deep expertise in AI/ML technologies, large language models, and generative AI.
• Exceptional communication skills to educate and influence at all organizational levels.
• 12+ years of progressive technology and AI leadership experience.

Responsibilities

• Define and execute enterprise AI strategy across tools and services.
• Drive organization-wide AI adoption through training and resources.
• Establish comprehensive AI governance covering compliance and safety.

Skills

AI/ML technologies

Communication skills

Strategic thinking

Partner management

AI platform architecture

Education

Bachelor's degree in Computer Science

Master's or PhD in AI/ML

Job description

The SVP, Chief AI Officer is accountable for AI strategy, governance, and measurable business impact across Rackspace. This executive leader defines the enterprise AI strategy spanning internal productivity tools, customer offerings, and managed services while operating the AI platform layer and establishing comprehensive AI governance. Reporting to the CEO, the CAIO drives AI adoption, manages AI economics, leads partner co‑innovation, and ensures responsible AI practices throughout the organization.

Responsibilities

• Define and execute enterprise AI strategy across internal productivity tools, customer offerings, and managed services
• Operate the AI platform layer, including model management, tooling, data pipelines, guardrails, and evaluation frameworks
• Drive organization‑wide AI adoption through fluency programs, training, playbooks, and industry‑specific solution accelerators
• Establish comprehensive AI governance covering risk management, compliance, security, safety, and model lifecycle management
• Own AI cost modeling and unit economics in partnership with Finance and Operations teams
• Manage GPU and CPU capacity strategy to optimize performance and cost

AI Strategy & Business Impact

• Own the AI platform roadmap, model portfolio, and evaluation and monitoring approaches
• Drive AI solution patterns for priority industries and embed AI capabilities into every product and service offering
• Measure and report AI value creation, including revenue impact, margin improvement, productivity gains, quality enhancements, and risk reduction
• Lead co‑innovation initiatives with key technology partners and AI vendors
• Coordinate AI go‑to‑market strategy with Product and Sales organizations

AI Governance & Responsible AI

• Set comprehensive policies for responsible AI including ethical use, bias mitigation, and fairness
• Establish data usage policies, privacy protections, and regulatory compliance frameworks
• Define AI safety standards and incident response protocols
• Create transparency and explainability requirements for AI systems
• Monitor and enforce adherence to AI governance policies across the organization

CTO Collaboration & Platform Integration

• Ensure AI platform standards align with overall technology architecture established by the CTO
• Obtain joint approval with CTO for AI architectures that impact core platform decisions or risk posture
• Participate in quarterly technology and AI strategy reviews with integrated roadmaps
• Co‑lead monthly architecture and model governance councils
• Coordinate on platform reliability, security, and cost optimization initiatives

Key Performance Indicators

• AI‑attributed revenue and pipeline contribution
• AI‑driven productivity improvements and cost savings
• AI adoption metrics across internal teams and customer base
• Model quality, performance, and safety scores
• AI platform reliability and uptime
• Cost per AI inference or transaction
• Compliance with AI governance policies and regulations
• Partner ecosystem engagement and co‑innovation outcomes
• Customer satisfaction with AI‑powered solutions

About Rackspace Technology

We are the multicloud solutions experts. We combine our expertise with the world's leading technologies – across applications, data and security – to deliver end‑to‑end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world‑class talent. Join us on our mission to embrace technology, empower customers and deliver the future.

Eligibility and EEO Statement

We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.

Qualifications

• Deep expertise in AI/ML technologies, large language models, and generative AI
• Strong understanding of AI platform architecture, MLOps, and model lifecycle management
• Knowledge of AI safety, bias mitigation, explainability, and responsible AI practices
• Familiarity with cloud infrastructure, data engineering, and modern software development practices
• Understanding of AI regulatory landscape and compliance requirements
• Strategic thinker who can translate AI capabilities into business value and competitive advantage
• Exceptional communication skills with the ability to educate and influence at all organizational levels
• Proven ability to drive adoption and change management across large organizations
• Experience building and leading multidisciplinary AI teams, including researchers, engineers, and data scientists
• Track record of partner management and ecosystem development
• Strong business acumen with an **an** understanding of go‑to‑market and monetization strategies
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field required
• Advanced degree (Master's or PhD) in AI, Machine Learning, Computer Science, or related field strongly preferred
• MBA or equivalent business education a plus
• 12+ years of progressive technology and AI leadership experience with at least 5 years in senior executive roles
• Proven track record building and scaling AI/ML platforms, products, or practices in enterprise environments
• Experience driving AI strategy that delivers measurable business outcomes and revenue impact
• History of establishing AI governance frameworks and responsible AI programs
• Experience managing large‑scale AI infrastructure, model operations, and GPU/compute resources