> Markdown version of [/jobs/ext/4469460-solution-enterprise-architect-database-l2](https://www.wearedevelopers.com/jobs/ext/4469460-solution-enterprise-architect-database-l2). 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). --- # Solution Enterprise Architect - Database L2 - **Company:** Capgemini - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Salary:** $76,918.0 - $120,203.0 - **Contract:** Temporary contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Applications Architecture, BigQuery, Cloud Engineering, Databases, Information Engineering, Identity and Access Management, Python (Programming Language), Machine Learning, Tensorflow, Gemini Enterprise (Agent Platform), Software Engineering, Systems Integration, Enterprise Search, Google Cloud, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Generative AI, Agentic-AI, AI Platforms, Scikit Learn, Machine Learning Operations, Gsuite, Api Design, Serverless Computing, Microservices - **Published:** October 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3f492bdeb3fbf7cc ## About the Role * 7+ years of experience in Software Engineering, AI Engineering, or Machine Learning Engineering * Hands-on experience designing and deploying enterprise-grade Generative AI solutions * Direct experience with Gemini Enterprise or comparable enterprise GenAI platforms * Strong expertise with Google Cloud Platform, including Vertex AI, BigQuery, Cloud Run, GKE, IAM, and cloud-native services * Advanced Python programming experience and proficiency with frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, and LangGraph * Strong understanding of Large Language Models, embeddings, vector databases, prompt engineering, fine-tuning, and RAG architectures * Experience deploying, monitoring, and supporting AI/ML solutions in production environments * Strong understanding of API development, microservices, and cloud-native application architecture * Excellent communication skills with the ability to work directly with customers and business stakeholders ## Description We are seeking an experienced AI Engineer to design, build, and scale enterprise-grade AI/ML solutions with a focus on Generative AI and Google Cloud Platform (GCP). This role will be responsible for developing customer-facing AI applications, leveraging Gemini Enterprise, Vertex AI, and modern LLM architectures to deliver scalable, secure, and production-ready solutions. The ideal candidate combines deep technical expertise with the ability to engage directly with customers and stakeholders to solve complex business challenges through AI., * Design, develop, and deploy AI/ML and Generative AI solutions for enterprise customers * Architect and implement solutions leveraging Gemini Enterprise, including AI agents, grounding, enterprise search, and Google Workspace integrations * Build and productionize scalable ML pipelines, APIs, and AI services using Python * Design and implement Retrieval-Augmented Generation (RAG) architectures, agentic workflows, and LLM-powered applications * Deploy, monitor, and optimize AI solutions across GCP services including Vertex AI, BigQuery, Cloud Run, GKE, Cloud Functions, and Pub/Sub * Collaborate with customers and stakeholders to gather requirements and translate business needs into scalable AI solutions * Partner with Data Engineering, MLOps, and Platform teams to integrate AI capabilities into enterprise environments * Ensure solutions meet standards for security, scalability, reliability, performance, and cost optimization * Evaluate emerging GCP AI technologies and recommend adoption where appropriate * Mentor junior engineers and contribute to AI/ML engineering best practices