Head of AI

About Atos Group

Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. €10 billion, operating in 61 countries under two brands — Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Position Head of Artificial Intelligence

Role Summary

The Head of Artificial Intelligence Practice (North America) leads strategy, growth, delivery excellence, and talent for the AI portfolio across U.S. and Canada. This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, 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 (solution leads, delivery leaders, architects), plus dotted-line matrix teams
• Geography United States and Canada (remote/hybrid depending on location)
• Travel Up to 25–40% (client sites, executive briefings, industry events)
  
  
  

Key Responsibilities

• Practice strategy and roadmap
• Define the North America AI practice strategy aligned to corporate goals and market demand.
• Build and maintain a 12–24 month capability roadmap across GenAI, Agentic AI, applied ML, AI engineering, MLOps, and AI governance.
• Identify strategic bets (industries, partnerships, platforms) and prioritize investments for impact and scale.
• Lead the delivery team for AI across NA including building and managing talent and ensuring ulitization targets for the team
• Portfolio, offerings, and thought leadership
• Support Head of Advisory and Global Teams with packaged offerings and accelerators (POCs-to-production playbooks, reference architectures, reusable components).
• Work with Head of Innovation industry-specific solutions (e.g., banking, retail, healthcare, telecom, public sector) with measurable outcomes.
• Represent the company externally through speaking, publishing, analyst briefings, and customer success stories.
• Go-to-market and revenue growth
• Own pipeline and bookings targets for AI services in North America; partner with sales, alliances, and marketing.
• Help Represent the solutioning for strategic pursuits, including executive-level proposal narratives, value cases, and pricing models.
• Help support the partner ecosystem with hyperscalers and AI platform vendors; drive co-sell motions where applicable.
• Delivery excellence and customer outcomes
• Ensure high-quality delivery across AI engagements, with strong governance, risk management, and stakeholder communication.
• Standardize delivery methodology for AI programs (discovery, prototyping, productionization, monitoring, continuous improvement).
• Drive customer adoption, measurable business value, and referenceability through disciplined success management.
• Talent, org design, and culture
• Build and scale a high-performing AI team hiring plans, skills frameworks, career paths, and mentorship.
• Upskill broader delivery teams through training programs, communities of practice, and internal enablement.
• Foster a culture of engineering rigor, responsible AI, collaboration, and continuous learning.
• Governance, security, and responsible AI
• Establish responsible AI standards (privacy, security, bias mitigation, explainability, model risk management).
• Partner with security, legal, and compliance teams to ensure AI solutions meet client and regulatory requirements.
• Define and monitor AI practice quality standards, including data governance, model lifecycle controls, and audits.
• Financial management and operations
• Help support the Head of Data and AI P&L revenue, gross margin, utilization, bench, subcontractor mix, and investment planning.
• Set operating rhythm QBRs, forecast accuracy, capacity planning, and delivery health dashboards.
• Optimize delivery model (onshore/nearshore/offshore) to meet client needs and margin targets.
  

Required Qualifications

• 15 years of experience in technology consulting, product engineering, or enterprise technology leadership, with 8 years in AI/ML/GenAI leadership.
• Proven track record building and scaling an AI practice or portfolio with P&L responsibility and measurable revenue growth.
• Strong understanding of modern AI stack GenAI (LLMs), Agentic AI, ML, data engineering, AI platforms, MLOps/LLMOps, and cloud services (AWS/Azure/GCP).
• Demonstrated experience delivering AI solutions end-to-end discovery to production, monitoring, and continuous improvement.
• Executive presence with ability to influence EVP-level stakeholders and lead complex deal pursuits.
• Experience leading multi-disciplinary teams (AI Architects, AI Engineers, data scientists, ML engineers, architects, product managers, delivery leaders).
• Knowledge of responsible AI, security, and privacy requirements for enterprise AI implementations.
  
  
  

Preferred Qualifications

• Experience in IT services/consulting organizations operating with global delivery models (onshore/nearshore/offshore).
• Domain expertise in one or more regulated industries (financial services, healthcare, telecom, government).
• Partnership experience with hyperscalers and AI platform vendors; co-sell and alliance management success.
• Hands-on experience with AI solution architecture, including retrieval-augmented generation (RAG), vector databases, and agentic workflows.
• Advanced degree in Computer Science, Engineering, Data Science, or related field; MBA a plus.
  
  
  

Core Competencies

• Strategic leadership and business building
• Consultative selling and executive stakeholder management
• AI engineering rigor and delivery governance
• Productization mindset (offerings, accelerators, repeatability)
• Talent development and organizational design
• Cross-functional collaboration in matrix environments
• Strong communication narrative building, proposals, and presentations
  
  
  

Tools and Technologies (Representative)

• Cloud AWS, Microsoft Azure, Google Cloud Platform
• AI/ML Agentic AI, Python, PyTorch/TensorFlow, scikit-learn, MLflow (or equivalent), feature stores
• GenAI LLM APIs and platforms, prompt engineering, RAG patterns, evaluation frameworks, guardrails
• Data SQL, modern data warehouses/lakehouse platforms, streaming where needed
• MLOps/LLMOps CI/CD for models, monitoring/observability, model registry, governance tooling
  
  
  

Work Environment

• Remote or hybrid within North America; may require proximity to major client hubs.
• Travel expectation up to 25–40% based on client needs and business development cycles.
• This role may require occasional work outside standard business hours to support executive meetings across time zones.
  
  
  

Equal Opportunity

The organization is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.

Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.

Choose your future. Choose Atos.