> Markdown version of [/jobs/ext/4023084-lead-data-scientist](https://www.wearedevelopers.com/jobs/ext/4023084-lead-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Scientist - **Company:** Capgemini - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $117,930.0 - $223,591.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Engineering, Information Engineering, Open Source Technology, OpenAI, Software Deployment, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Snowflake, Google Vertex AI, IT Architecture, Llamaindex, Generative AI, Agentic-AI, Togaf, Event Driven Architecture, Microsoft Fabric, Machine Learning Operations, Semantic Kernel, Databricks - **Published:** October 30, 2026 - **Apply:** https://www.capgemini.com/jobs/580551-en_US_SAPBTP/x/ ## About the Role * 10+ years of experience in Solution Architecture, Enterprise Architecture, Cloud Architecture, or Platform Architecture. * 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. Technical Expertise * 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) + 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 + API and event-driven architectures * Strong understanding of cybersecurity, privacy, governance, and Responsible AI principles. Leadership Skills * 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., * 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. * Contributions to industry thought leadership 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 + Microsoft Fabric ## Description Capgemini is seeking a highly experienced Managing AI Architect / Principal AI Architect to lead the architecture of our largest and most strategic AI transformation programs. This is a senior leadership role responsible for shaping and governing complex, enterprise-scale AI, Generative AI, and Agentic AI solutions from initial client pursuit through production deployment and operationalization. You will work directly with CIOs, CTOs, CDOs, and senior business leaders, providing strategic guidance on AI architecture, platform choices, delivery approaches, and business value realization. As the accountable architecture leader, you will ensure that every proposed solution is secure, scalable, cost-effective, responsible, and deliverable. This role combines executive advisory, enterprise architecture leadership, pursuit support, delivery governance, and AI capability development.