Lead Data Scientist
About The Position
Capgemini is seeking an experienced AI architecture leader to shape and govern complex, enterprise-scale AI, Generative AI, and Agentic AI transformation programs, from client pursuit through production deployment and operationalization. The role provides strategic guidance to senior business and technology leaders on AI architecture, platform selection, delivery approaches, and business value realization, while ensuring proposed solutions are secure, scalable, cost-effective, responsible, and deliverable. The position combines executive advisory, enterprise architecture leadership, pursuit support, delivery governance, and AI capability development. It involves leading architecture for large enterprise transformation programs, contributing to opportunities and proposals, governing solutions, and guiding distributed teams in complex, multi-vendor environments. The posting lists locations in Chicago, Illinois; Atlanta, Georgia; and New York, New York.
Requirements
- 10 or more years of experience in solution architecture, enterprise architecture, cloud architecture, or platform architecture.
- At least 3 years of hands-on experience designing and delivering AI/ML, Generative AI, or Agentic AI solutions in production environments.
- Proven experience owning architecture for complex enterprise transformation programs.
- Strong consulting background with extensive client-facing and executive stakeholder engagement.
- Demonstrated success shaping large opportunities and supporting proposal development and solution governance.
- Deep understanding of enterprise AI architecture and modern AI platforms.
- Experience with at least one major hyperscaler AI ecosystem: Microsoft Azure AI, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- Knowledge of large language models (LLMs), RAG architectures, Agentic AI frameworks, vector databases and knowledge platforms, MLOps and LLMOps, data engineering and integration architectures, and API and event-driven architectures.
- Strong understanding of cybersecurity, privacy, governance, and Responsible AI principles.
- Executive presence and ability to influence senior stakeholders.
- Strong architectural governance and decision-making capabilities.
- Exceptional communication, facilitation, and stakeholder management skills.
- Ability to lead distributed teams across complex, multi-vendor environments.
Nice To Haves
- Experience across multiple hyperscaler cloud platforms.
- Experience delivering AI solutions in regulated industries such as Financial Services, Healthcare, Life Sciences, Telecommunications, Energy, or Public Sector.
- TOGAF, Azure, AWS, or GCP architecture certifications.
- Experience developing enterprise reference architectures and reusable AI assets.
- Industry thought leadership contributions through publications, patents, open-source projects, conference presentations, or industry forums.
- Experience with modern AI frameworks and platforms such as Azure AI Foundry, OpenAI Services, AWS Bedrock, Google Vertex AI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, Databricks, Snowflake, and Microsoft Fabric.
Responsibilities
- Lead architecture for strategic enterprise AI transformation programs from client pursuit through production deployment and operationalization.
- Advise CIOs, CTOs, CDOs, and senior business leaders on AI architecture, platform choices, delivery approaches, and business value realization.
- Ensure proposed solutions are secure, scalable, cost-effective, responsible, and deliverable.
- Own architecture for complex enterprise transformation programs.
- Shape large opportunities and support proposal development and solution governance.
- Provide architectural governance and decision-making across programs.
- Lead distributed teams across complex, multi-vendor environments.
- Develop enterprise reference architectures and reusable AI assets (preferred qualification).
Benefits
- Paid time off based on employee grade: 12–25 vacation days depending on grade, company-paid holidays, personal days, and sick leave.
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).
- Retirement savings plans, such as 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.
- May be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
