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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.

• 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)

• • 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

• • 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.

• • 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.

• • 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.

• • 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.

• • 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.

• • 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.

• 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.

• 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

• 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

• 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.