Lead Data Scientist

Capgemini•Chicago, IL

13d•$150,000 - $210,000•Onsite

About The Position

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. We are seeking a highly experienced Senior AI Architect / Lead Engineer to lead the design, architecture, and development of next-generation AI-powered Customer Experience (CX) platforms. This role is ideal for a hands-on technology leader who combines deep expertise in Agentic AI, Generative AI, Large Language Models (LLMs), and Google Cloud AI services with a strong background in customer engagement and contact center solutions. The successful candidate will drive the technical vision and implementation of intelligent, autonomous customer experience platforms leveraging multi-agent systems, Retrieval-Augmented Generation (RAG), workflow automation, and Google Cloud AI technologies. This individual must be equally comfortable defining enterprise architecture, mentoring engineering teams, and writing production-grade code.

Requirements

10+ years of software engineering, cloud architecture, or enterprise solution design experience
5+ years of AI/ML or Generative AI experience
Proven experience delivering enterprise-scale AI applications on Google Cloud
Strong Python development skills
Leadership and mentoring experience
Strong Agentic AI expertise
Deep GenAI, LLM, and RAG experience
Extensive Google Cloud and Vertex AI experience
Customer Experience / Contact Center domain expertise
Hands-on architect who still codes
Strong system design and microservices architecture skills
Proven leadership and mentoring experience

Nice To Haves

Multi-agent systems and autonomous AI agents
LangChain
LlamaIndex
Semantic Kernel
CrewAI
AutoGen
Vertex AI Agent Builder
Tool-calling agents and workflow automation
Retrieval-Augmented Generation (RAG)
Prompt engineering
AI evaluation and governance
Google Gemini models
PaLM models
Enterprise LLM integration patterns
Vertex AI (Gemini/PaLM)
Vertex AI Agent Builder
Dialogflow CX
BigQuery
Pub/Sub
Cloud Run
Google Kubernetes Engine (GKE)
Cloud Functions

Responsibilities

Define and execute the architecture strategy for AI-powered CX and contact center solutions.
Design, build, and deploy Agentic AI systems using autonomous agents, multi-agent collaboration, and workflow orchestration frameworks.
Develop intelligent conversational and task-oriented experiences leveraging LLMs and Generative AI technologies.
Architect scalable and secure AI solutions on Google Cloud Platform (GCP).
Build and optimize RAG pipelines for enterprise knowledge retrieval and contextual AI interactions.
Design agent workflows incorporating tool usage, API integrations, function calling, and orchestration capabilities.
Lead the implementation of cloud-native microservices and event-driven architectures.
Collaborate with business, CX, product, and engineering stakeholders.
Establish AI architecture standards, development best practices, governance, and security controls.
Mentor engineers and architects while providing technical leadership