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# Lead Data Scientist

- **Company:** Capgemini
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $109,180.0 - $197,175.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Engineering, Data Integration, Knowledge-Based Systems, Software Deployment, Google Cloud, Retrieval-Augmented Generation, Large Language Models, IT Architecture, Togaf, Data Management, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://www.capgemini.com/jobs/579117-en_US_SAPBTP/x/

## About the Role

* 10+ years in solution, enterprise, platform or cloud architecture
 * 3+ years designing AI/ML or GenAI solutions, including production deployments
 * Proven ownership of complex enterprise architecture
 * Client-facing consulting and executive stakeholder experience
 * Production experience with at least one hyperscaler AI ecosystem
 * Evidence of solution shaping and delivery governance
 * Strong grounding in security, data, integration and Responsible AI

Desirable

 * Experience across more than one hyperscaler
 * Experience in regulated industries
 * TOGAF or hyperscaler architecture certifications
 * Experience creating reusable assets or reference architectures
 * Public thought leadership, patents, publications or conference participation
 * Knowledge of specific AI frameworks and data platforms

## Description

Own the AI architecture for Capgemini's largest and most strategic client programs. As a Managing AI Architect / Principal AI Architect, you will be accountable for the architecture of complex, multi-workstream AI, generative AI and agentic AI programs, from the first pursuit conversation through to production. You will advise CIOs, CTOs, CDOs and business executives, govern the decisions made by architecture teams, and make sure that what we propose is what we can deliver: secure, scalable, cost-effective and tied to measurable business outcomes.

 * Own end-to-end AI architecture across multiple workstreams or programs, spanning foundation models, RAG and knowledge systems, agents and orchestration, data and integration platforms, cloud and hybrid infrastructure, and MLOps/LLMOps, so the overall solution is coherent, scalable and aligned with enterprise architecture principles.
 * Lead AI solution shaping for strategic pursuits, defining the architecture, delivery approach, effort, risks, differentiators and commercial assumptions required to create credible and competitive proposals.
 * Advise CIOs, CTOs, CDOs and business executives on AI architecture strategy, platform and vendor choices across Azure, AWS, GCP and the wider AI ecosystem, and the roadmap from early use cases to enterprise scale.
 * Act as design authority, governing the decisions made by other architects, setting the standards, reference architectures and guardrails for security, privacy, Responsible AI and regulatory compliance, and carrying accountability for architecture quality and delivery risk.
 * Lead architecture through delivery, covering detailed design, engineering mobilization, implementation assurance, production readiness, transition into operations and remediation of architecture deviations.
 * Take responsibility for business outcomes, linking architecture decisions to measurable client value and applying FinOps discipline to forecast, monitor and optimize model, compute and platform costs from proposal through to operations.
 * Develop Capgemini's AI architecture capability by mentoring and growing architects, creating reference architectures, and building market credibility through alliances and thought leadership.