Principal AI Enterprise Architect

Capgemini • New York, NY

1d • $167,500 - $245,200 • Onsite

About The Position

Capgemini is seeking an accomplished Enterprise Architect specializing in Machine Learning, Agentic AI, and enterprise AI transformation. This leadership role defines and governs enterprise-wide AI architecture, advances the industrialization of AI capabilities, and enables business transformation through scalable, secure, and reusable AI platforms and assets. The architect advises senior leadership, business stakeholders, technology teams, and clients, aligning business objectives with AI investments and providing strategic direction, technical leadership, architecture governance, and delivery oversight.

The role is based in New York City and requires working onsite at the NYC office four days per week. It leads enterprise AI strategy and transformation, establishes architecture standards and governance, guides platform and solution design, and oversees adoption of cloud-native AI capabilities and operational practices. It also develops architects and engineering teams, supports strategic investment decisions, and represents the organization in client and industry forums.

The posted base compensation range is $167,500–$245,200 USD. Capgemini states that regular, full-time employees receive a comprehensive benefits package; benefits vary by local policy and eligibility and may include paid time off, holidays, personal and sick leave, medical, dental and vision coverage, retirement savings plans, life and disability insurance, and employee assistance programs.

Requirements

• Master’s degree in computer science, engineering, artificial intelligence, data science, information systems, or a related discipline.
• 20+ years of overall IT experience with strong expertise in Enterprise Architecture and AI-led digital transformation.
• Proven experience defining enterprise technology strategy and architecture governance frameworks.
• Deep expertise in enterprise generative AI and Agentic AI architecture patterns, including multi-agent systems, reasoning frameworks, orchestration architectures, RAG, knowledge engineering, AI platform design, model ecosystems, and LLM integration strategies.
• Demonstrated success delivering and scaling generative AI, Agentic AI, machine learning, and generative AI solutions in large enterprise environments.
• Experience leading architecture teams and influencing senior executives, clients, and cross-functional organizations.
• Strong background in enterprise modernization, cloud transformation, platform engineering, and AI industrialization.
• Deep expertise in generative or Agentic AI ecosystems, including OpenAI, Azure OpenAI, AWS Bedrock, GCP ADK, Claude, Gemini, Llama, LangChain, LangGraph, Agentic AI frameworks, and RAG architectures.
• Strong experience with MLOps, LLMOps, AI governance, model lifecycle management, monitoring, and observability.
• Familiarity with cybersecurity, regulatory compliance, data privacy, responsible AI, and risk management frameworks.
• Exceptional stakeholder management and executive communication skills.
• Strong strategic thinking and business acumen, with the ability to align technology investments to business outcomes.
• Proven ability to influence organizational decisions and drive enterprise-wide technology adoption.
• Strong leadership, mentoring, and talent development capabilities.
• Excellent problem-solving, decision-making, and analytical skills.
• Ability to operate effectively in complex, global, and matrix-based organizations.
• Strong customer-centric mindset and experience supporting client-facing engagements and executive presentations.
• Ability to work onsite at the New York City office four days per week.

Nice To Haves

• Ph.D. in AI, Machine Learning, Computer Science, or a related field is desirable.

Responsibilities

• Define and drive enterprise AI architecture strategy in alignment with organizational objectives, digital transformation initiatives, and technology roadmaps.
• Establish enterprise architecture standards, governance frameworks, and best practices for AI, ML, and generative AI solutions.
• Lead the design and evolution of scalable, secure, reusable, and future-ready AI platforms, frameworks, and accelerators.
• Drive industrialization and adoption of AI assets across business units, maximizing reuse and organizational value.
• Provide executive-level technology leadership and architectural guidance to business leaders, delivery organizations, and client stakeholders.
• Lead enterprise-wide AI transformation initiatives and identify opportunities for business growth, operational efficiency, and innovation through AI.
• Establish reference architectures, design patterns, and reusable frameworks for AI and generative AI solutions.
• Lead architecture reviews and ensure compliance with enterprise standards for security, privacy, risk management, and responsible AI.
• Collaborate with business stakeholders to define AI strategies, roadmap priorities, investment plans, and measurable business outcomes.
• Lead architecture governance boards and promote consistency across programs, products, and platforms.
• Evaluate emerging technologies, AI frameworks, foundation models, and industry trends to define future-state architecture.
• Drive cloud-native AI adoption using Azure, AWS, GCP, and modern platform engineering practices.
• Oversee enterprise AI platform deployment strategies, including MLOps, LLMOps, CI/CD, observability, monitoring, and operational excellence.
• Define data architecture principles and integration patterns that support AI-driven business capabilities.
• Mentor and develop architects, AI leaders, and engineering teams, fostering innovation, engineering excellence, and continuous learning.
• Partner with delivery and product teams to implement the architecture vision across strategic initiatives.
• Drive enterprise adoption of responsible AI practices and compliance with regulatory, security, privacy, and ethical requirements.
• Influence technology investment decisions and support business cases for strategic AI initiatives.
• Represent the organization in client engagements, executive architecture discussions, innovation forums, and industry thought leadership initiatives.
• Lead the definition and evolution of enterprise AI platforms, shared services, reusable agents, accelerators, and AI operating models.
• Define the enterprise AI operating model, governance structures, decision-making processes, and adoption framework for scalable AI transformation.
• Define enterprise standards and architecture patterns for Agentic AI, including multi-agent orchestration, memory frameworks, tool integration, human oversight, evaluation frameworks, observability, and lifecycle management.

Benefits

• Paid time off, with vacation of 12–25 days depending on employee grade, plus company-paid holidays, personal days, and sick leave.
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
• Retirement savings plans, such as a 401(k) in the U.S. or RRSP in Canada.
• Life and disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal