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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Engineer - Google Cloud Platform AI Architect - **Company:** Capgemini - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $144,890.0 - $190,117.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Computer Vision, BigQuery, Business Software, Cloud Computing, Cloud Engineering, Cloud Storage, Continuous Integration, Data Cleansing, Disaster Recovery, Data Flow Control, Machine Learning, Meta-Data Management, Natural Language Processing, Open Source Technology, Search Technologies, Software Engineering, Google Cloud, Feature Engineering, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Data Lakes, AI Platforms, Kubernetes, Data Analytics, Performance Monitor, Data Management, Machine Learning Operations, Virtual Agents - **Published:** August 15, 2026 - **Apply:** https://www.dice.com/job-detail/ae618e15-6933-4487-9ca5-cbe00d8578aa ## About the Role * 8+ years of experience in cloud architecture, software engineering, or data platforms. * 3+ years of experience designing AI/ML solutions on Google Cloud Platform. * Experience leading enterprise-scale cloud transformation programs. * Experience architecting Generative AI and LLM-based applications. * AI & Machine Learning - Machine Learning model lifecycle - Natural Language Processing (NLP) - Computer Vision ## Description We are seeking an experienced Google Cloud Platform AI Architect to lead the design, architecture, and implementation of enterprise-scale Artificial Intelligence (AI), Generative AI, Machine Learning (ML), and Data Analytics solutions on Google Cloud Platform (Google Cloud Platform). The ideal candidate will combine deep expertise in cloud architecture, AI/ML technologies, and business transformation to create scalable, secure, and responsible AI solutions that deliver measurable business value. Your Role * AI & Generative AI Architecture - Design end-to-end AI, Generative AI, and ML solution architectures on Google Cloud Platform. - Define enterprise AI strategies, roadmaps, and reference architectures. - Architect Retrieval-Augmented Generation (RAG), Agentic AI, and AI-powered business applications. - Evaluate and select appropriate Foundation Models, Gemini models, and open-source LLMs. - Design prompt engineering, fine-tuning, grounding, and vector search strategies. * Google Cloud Architecture - Design scalable, secure, and highly available cloud-native architectures using: - Vertex AI - BigQuery - Cloud Storage - Cloud Run - Google Kubernetes Engine (GKE) - Dataflow - Pub/Sub - Cloud Functions - Define multi-region and disaster recovery strategies. - Ensure architectural alignment with enterprise cloud standards. * AI Platform & MLOps - Establish enterprise MLOps and LLMOps frameworks. - Design automated model development, deployment, monitoring, and governance pipelines. - Define model lifecycle management processes. - Implement CI/CD practices for AI solutions. - Monitor performance, model drift, and operational efficiency. * Data & Analytics Architecture - Design modern data architecture supporting AI initiatives. - Create data lakes, lakehouses, and enterprise analytics solutions. - Establish feature engineering and data preparation frameworks. - Define data quality, governance, lineage, and metadata management practices. * Security, Governance & Responsible AI - Define AI governance frameworks and policies. - Implement data privacy, compliance, and security controls. - Ensure Responsible AI principles including: - Fairness - Transparency - Explainability - Bias detection - Risk mitigation - Collaborate with security and compliance teams., Large Language Models (LLMs) - Vertex AI Model Garden - Prompt Engineering - Fine-tuning Foundation Models - Vector Databases and Embeddings - RAG Architecture - AI Agents and Multi-Agent Systems * Preferred Certifications - Google Cloud Professional Cloud Architect - Google Cloud Professional Machine Learning Engineer - Google Cloud Professional Data Engineer ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [Got AI ideas but no money? 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