{"schemaVersion":"jobsearcher.job.v1","id":"41d97cbde00a52f322c2a260","url":"https://jobsearcher.com/jobs/41d97cbde00a52f322c2a260","canonicalUrl":"https://jobsearcher.com/jobs/41d97cbde00a52f322c2a260","title":"AI Architect - Google AI & Generative Intelligence","description":"Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sincera Technologies, Inc., is seeking the following. Apply via Dice today!We are seeking a highly accomplished AI Architect with deep expertise in Google AI technologies and Generative AI to lead the design and implementation of enterprise-scale AI solutions. This role requires strong architectural vision, hands-on technical depth, and leadership in building production-grade AI systems leveraging LLMs, SLMs, and multi-agent frameworks.The ideal candidate will drive AI strategy, define scalable architectures, and lead cross-functional teams in delivering cutting-edge AI-powered applications using the Google Cloud ecosystem, modern AI frameworks, and robust MLOps practices.Key Responsibilities: AI Architecture & StrategyDefine end-to-end AI/GenAI architecture for enterprise-grade applications.Establish best practices for LLM/SLM adoption, multi-agent systems, and RAG architectures.Drive AI platform strategy leveraging Google Cloud (Vertex AI, GKE, Cloud Run).Lead architecture reviews, technical governance, and design standards. LLM / SLM & Generative AI SolutionsArchitect solutions using commercial LLMs such as Gemini, GPT, and Claude.Design scalable systems using open-source models (Mixtral, Mistral, Gemma, Phi-3).Define strategies for fine-tuning (LoRA, QLoRA, PEFT) and model optimization.Oversee model evaluation frameworks and benchmarking (HELM, lm-eval, RAGAS). Google AI Ecosystem LeadershipLead adoption of:Vertex AI for model lifecycle managementGoogle Agent Development Kit (ADK) for intelligent agentsGoogle Workspace integrations (Docs, Sheets, Gmail, Drive, Meet)Architect solutions using BigQuery, Lakehouse, and Vector Databases. AI Platform & MLOps ArchitectureDesign scalable MLOps pipelines for training, deployment, and monitoring.Define CI/CD strategies for AI systems using GitHub Actions / GitLab CI.Establish observability frameworks using LangSmith, MLflow, Weights & Biases.Optimize infrastructure cost and performance across cloud and hybrid environments. Multi-Agent Systems & AI FrameworksArchitect complex workflows using:LangChain, LlamaIndex, LangGraphSemantic Kernel for multi-agent orchestrationDesign intelligent automation pipelines and agent collaboration patterns. Data & RAG ArchitectureDesign enterprise RAG pipelines using Vertex AI Vector DB, ChromaDB.Define data ingestion, transformation, and governance strategies.Architect semantic search and knowledge retrieval systems. Application & Integration ArchitectureDefine backend architecture using FastAPI / Node.js APIs.Architect API management and security using Apigee / MuleSoft.Guide frontend architecture using React / Angular for AI-driven applications. Engineering LeadershipProvide technical leadership and mentorship to AI/ML engineers.Collaborate with product, data, and engineering teams for solution delivery.Lead design documentation, architecture diagrams, and technical roadmaps.Ensure adherence to coding standards, testing, and quality frameworks. Deployment & InfrastructureArchitect deployments across:Google Cloud Platform (Vertex AI, GKE, Cloud Run)Hybrid and on-prem environmentsEdge AI use casesEnsure scalability, reliability, and security of AI systems. AI Governance & Responsible AIDefine frameworks for AI ethics, bias mitigation, and explainability.Establish governance for model lifecycle, monitoring, and compliance.Implement safeguards for hallucination detection and output validation.Required Qualifications:12 18 years of software engineering experience.7+ years in AI/ML with strong focus on Generative AI and LLMs.Deep expertise in Google AI ecosystem (Vertex AI, Gemini, ADK, AI Studio).Strong experience in LLMs, SLMs, RAG, and multi-agent architectures.Proficiency in Python and familiarity with Node.js.Hands-on experience with MLOps, CI/CD, and cloud-native architecture (Google Cloud Platform).Proven experience designing scalable, production-grade AI systems.Preferred Qualifications:Google Cloud Certifications (Professional ML Engineer / Cloud Architect).Experience contributing to open-source AI/ML projects.Expertise in edge AI and hybrid cloud deployments.Experience building enterprise AI platforms or COEs.Strong leadership experience mentoring and scaling AI teams.Key Skills Summary:Generative AI (LLMs, SLMs, RAG, Agents)Google Cloud AI Stack (Vertex AI, Gemini, ADK)AI Frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel)MLOps & Observability (MLflow, W&B, LangSmith)Cloud & Infrastructure (Google Cloud Platform, Kubernetes, Serverless)Backend & APIs (FastAPI, Node.js, Apigee)Data & Vector DBs (BigQuery, ChromaDB, Vector Search)","company":"Via Dice","rawCompany":"via dice","city":"Paramus","state":"NJ","isRemote":false,"isActive":false,"createdAt":"2026-04-12T19:43:21.352Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Architect - Google AI & Generative Intelligence","description":"Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sincera Technologies, Inc., is seeking the following. Apply via Dice today!We are seeking a highly accomplished AI Architect with deep expertise in Google AI technologies and Generative AI to lead the design and implementation of enterprise-scale AI solutions. This role requires strong architectural vision, hands-on technical depth, and leadership in building production-grade AI systems leveraging LLMs, SLMs, and multi-agent frameworks.The ideal candidate will drive AI strategy, define scalable architectures, and lead cross-functional teams in delivering cutting-edge AI-powered applications using the Google Cloud ecosystem, modern AI frameworks, and robust MLOps practices.Key Responsibilities: AI Architecture & StrategyDefine end-to-end AI/GenAI architecture for enterprise-grade applications.Establish best practices for LLM/SLM adoption, multi-agent systems, and RAG architectures.Drive AI platform strategy leveraging Google Cloud (Vertex AI, GKE, Cloud Run).Lead architecture reviews, technical governance, and design standards. LLM / SLM & Generative AI SolutionsArchitect solutions using commercial LLMs such as Gemini, GPT, and Claude.Design scalable systems using open-source models (Mixtral, Mistral, Gemma, Phi-3).Define strategies for fine-tuning (LoRA, QLoRA, PEFT) and model optimization.Oversee model evaluation frameworks and benchmarking (HELM, lm-eval, RAGAS). Google AI Ecosystem LeadershipLead adoption of:Vertex AI for model lifecycle managementGoogle Agent Development Kit (ADK) for intelligent agentsGoogle Workspace integrations (Docs, Sheets, Gmail, Drive, Meet)Architect solutions using BigQuery, Lakehouse, and Vector Databases. AI Platform & MLOps ArchitectureDesign scalable MLOps pipelines for training, deployment, and monitoring.Define CI/CD strategies for AI systems using GitHub Actions / GitLab CI.Establish observability frameworks using LangSmith, MLflow, Weights & Biases.Optimize infrastructure cost and performance across cloud and hybrid environments. Multi-Agent Systems & AI FrameworksArchitect complex workflows using:LangChain, LlamaIndex, LangGraphSemantic Kernel for multi-agent orchestrationDesign intelligent automation pipelines and agent collaboration patterns. Data & RAG ArchitectureDesign enterprise RAG pipelines using Vertex AI Vector DB, ChromaDB.Define data ingestion, transformation, and governance strategies.Architect semantic search and knowledge retrieval systems. Application & Integration ArchitectureDefine backend architecture using FastAPI / Node.js APIs.Architect API management and security using Apigee / MuleSoft.Guide frontend architecture using React / Angular for AI-driven applications. Engineering LeadershipProvide technical leadership and mentorship to AI/ML engineers.Collaborate with product, data, and engineering teams for solution delivery.Lead design documentation, architecture diagrams, and technical roadmaps.Ensure adherence to coding standards, testing, and quality frameworks. Deployment & InfrastructureArchitect deployments across:Google Cloud Platform (Vertex AI, GKE, Cloud Run)Hybrid and on-prem environmentsEdge AI use casesEnsure scalability, reliability, and security of AI systems. AI Governance & Responsible AIDefine frameworks for AI ethics, bias mitigation, and explainability.Establish governance for model lifecycle, monitoring, and compliance.Implement safeguards for hallucination detection and output validation.Required Qualifications:12 18 years of software engineering experience.7+ years in AI/ML with strong focus on Generative AI and LLMs.Deep expertise in Google AI ecosystem (Vertex AI, Gemini, ADK, AI Studio).Strong experience in LLMs, SLMs, RAG, and multi-agent architectures.Proficiency in Python and familiarity with Node.js.Hands-on experience with MLOps, CI/CD, and cloud-native architecture (Google Cloud Platform).Proven experience designing scalable, production-grade AI systems.Preferred Qualifications:Google Cloud Certifications (Professional ML Engineer / Cloud Architect).Experience contributing to open-source AI/ML projects.Expertise in edge AI and hybrid cloud deployments.Experience building enterprise AI platforms or COEs.Strong leadership experience mentoring and scaling AI teams.Key Skills Summary:Generative AI (LLMs, SLMs, RAG, Agents)Google Cloud AI Stack (Vertex AI, Gemini, ADK)AI Frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel)MLOps & Observability (MLflow, W&B, LangSmith)Cloud & Infrastructure (Google Cloud Platform, Kubernetes, Serverless)Backend & APIs (FastAPI, Node.js, Apigee)Data & Vector DBs (BigQuery, ChromaDB, Vector Search)","datePosted":"2026-04-12T19:43:21.352Z","dateModified":"2026-04-12T19:43:21.352Z","hiringOrganization":{"@type":"Organization","name":"Via Dice","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paramus","addressRegion":"NJ","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"41d97cbde00a52f322c2a260"},"url":"https://jobsearcher.com/jobs/41d97cbde00a52f322c2a260"}}