JD -
We are seeking an experienced Gemini AI & Google Cloud Platform (Google Cloud Platform) Architect to lead the design, architecture, and implementation of enterprise-scale Generative AI solutions on Google Cloud. The ideal candidate should have deep expertise in Geminimodels, Vertex AI, AI Agents, GenAI architecture patterns, and cloud-native solution design, with the ability to drive AI transformation initiatives across multiple business functions.
Key Responsibilities:
Define and lead the architecture strategy for Gemini-based AI solutions on Google Cloud Platform.
Design scalable, secure, and cost-optimized Generative AI platforms leveraging Vertex AI and Gemini models.
Architect RAG frameworks integrating enterprise data sources, vector databases, and knowledge repositories.
Design and implement intelligent AI agents, copilots, virtual assistants, and automation solutions. Establish AI governance, security, compliance, and Responsible AI best practices.
Collaborate with business stakeholders to identify high-value AI use cases and establish implementation roadmaps.
Lead cloud-native solution architecture using Google Cloud Platform services and microservices frameworks.
Provide technical leadership for AI/ML development teams and conduct architecture reviews.
Drive MLOps and operational excellence for AI model deployment, monitoring, and optimization. Evaluate emerging AI technologies and recommend innovative solutions aligned with business goals. Ensure AI solutions meet enterprise scalability, reliability, and performance requirements.
Required Skills:
Strong expertise in Google Cloud Platform (Google Cloud Platform) Architecture
Hands-on experience with Google Gemini Models and Vertex AI
- Expertise in Generative AI, LLMs, NLP, and Multimodal AI Experience designing RAG (Retrieval-Augmented Generation) solutions Knowledge of Agentic AI, AI Agents, and Agent Development Kit (ADK) Strong proficiency in Python, API development, and cloud-native applications Experience with Vector Databases (Vertex AI Vector Search, Pinecone, ChromaDB, etc.) Expertise in Cloud Run, Kubernetes (GKE), BigQuery, Pub/Sub, Cloud Functions, GCS Understanding of AI governance, security, compliance, and Responsible AI Experience with MLOps, CI/CD, model monitoring, and AI lifecycle management Enterprise integration experience with CRM, ERP, and business applications
Preferred
Qualifications: Experience with LangChain, LlamaIndex, CrewAI, AutoGen, or similar AI orchestration frameworks Multi-cloud AI architecture exposure (Azure OpenAI, AWS Bedrock) Google Cloud Platform Professional Cloud Architect Certification Generative AI Leader or Vertex AI related certifications Experience in AI Center of Excellence (CoE) initiative
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