About Atos Group
Atos Group is a global leader in digital transformation with approximately 67,000 employees and annual revenue of approximately €10 billion, operating in 61 countries under two brands—Atos for services and Eviden for products. The Group provides AI-powered, end-to-end solutions across industries and is a leader in cybersecurity, cloud, and high performance computing.
Role Summary
The Head of Artificial Intelligence Practice (North America) leads strategy, growth, delivery excellence, and talent for the AI portfolio across the United States and Canada. This executive role owns practice P&L, builds scalable offerings across GenAI, ML, data science, AI platforms, and MLOps, and partners with sales and delivery leaders to expand revenue and customer impact across industries.
Reporting and Scope
- Reports to: Head of Data & AI—North America
- Direct reports: AI practice leadership team, including solution leads, delivery leaders, and architects, plus dotted-line matrix teams
- Geography: United States and Canada
- Travel: Up to 25–40% for client sites, executive briefings, and industry events
Key Responsibilities
- Define the North America AI practice strategy and maintain a 12–24 month capability roadmap across GenAI, Agentic AI, applied ML, AI engineering, MLOps, and AI governance.
- Lead the AI delivery team across North America, including talent management and utilization targets.
- Develop packaged offerings, accelerators, POCs-to-production playbooks, reference architectures, and reusable components.
- Work with industry leaders to create solutions for sectors including banking, retail, healthcare, telecom, and the public sector.
- Represent the company through speaking, publishing, analyst briefings, and customer success stories.
- Own pipeline and bookings targets for AI services in North America and support strategic pursuits, proposals, value cases, pricing models, alliances, and co-sell motions.
- Ensure high-quality delivery through governance, risk management, standardized methodologies, customer adoption, and measurable business value.
- Build and scale a high-performing AI team through hiring plans, skills frameworks, career paths, mentorship, training, and communities of practice.
- Establish responsible AI standards covering privacy, security, bias mitigation, explainability, model risk management, data governance, lifecycle controls, and audits.
- Support P&L management, including revenue, gross margin, utilization, bench, subcontractor mix, and investment planning.
- Establish operating rhythms such as QBRs, forecasting, capacity planning, and delivery health dashboards.
Required Qualifications
- 15+ years of experience in technology consulting, product engineering, or enterprise technology leadership, with 8+ years in AI, ML, or GenAI leadership.
- Experience building and scaling an AI practice or portfolio with P&L responsibility and measurable revenue growth.
- Strong understanding of GenAI, LLMs, Agentic AI, ML, data engineering, AI platforms, MLOps/LLMOps, and AWS, Azure, or Google Cloud.
- Experience delivering AI solutions end-to-end, from discovery through production, monitoring, and continuous improvement.
- Executive presence and the ability to influence EVP-level stakeholders and lead complex deal pursuits.
- Experience leading multidisciplinary teams of AI architects, AI engineers, data scientists, ML engineers, architects, product managers, and delivery leaders.
- Knowledge of responsible AI, security, and privacy requirements for enterprise AI implementations.
Preferred Qualifications
- Experience in IT services or consulting organizations using global delivery models.
- Domain expertise in regulated industries such as financial services, healthcare, telecom, or government.
- Partnership experience with hyperscalers and AI platform vendors.
- Hands-on experience with RAG, vector databases, and agentic workflows.
- Advanced degree in Computer Science, Engineering, Data Science, or a related field; MBA is a plus.
Tools and Technologies
- Cloud: AWS, Microsoft Azure, Google Cloud Platform
- AI/ML: Agentic AI, Python, PyTorch/TensorFlow, scikit-learn, MLflow, and feature stores
- GenAI: LLM APIs and platforms, prompt engineering, RAG patterns, evaluation frameworks, and guardrails
- Data: SQL, modern data warehouses and lakehouse platforms, and streaming technologies
- MLOps/LLMOps: Model CI/CD, monitoring, observability, model registries, and governance tooling
Work Environment
Remote or hybrid within North America, with possible proximity to major client hubs. Travel may be required up to 25–40% based on client needs and business development cycles. Occasional work outside standard business hours may be required to support executive meetings across time zones.
Equal Opportunity
Atos is an equal opportunity employer committed to diversity, inclusion, and a fair work environment.