Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas

$120K — $150K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in a related field or equivalent experience
  • 5+ years in cloud architecture or AI/ML solution architecture
  • 3+ years with Google Cloud Platform
  • Hands-on experience with Gemini Enterprise or generative AI solutions
  • Strong coding skills in Python, JavaScript, or similar languages

Responsibilities

  • Design and implement Gemini Enterprise solutions for clients
  • Develop AI agent workflows for business use cases
  • Create prototypes and proofs of concept for production-ready solutions
  • Build LLM-powered applications and integrate AI agents
  • Evaluate various model options and integration paths for clients
  • Lead technical discovery sessions with clients to define solutions
  • Communicate complex technical recommendations to clients

Benefits

  • Opportunity to work on cutting-edge AI technologies
  • Emphasis on hands-on implementation rather than sales
  • Client-facing role that enhances communication and consulting skills
  • Work in a rapidly evolving tech environment with innovative solutions
Full Job Description
Google Cloud AI Solutions Architect, Gemini Enterprise Overview We are seeking a hands-on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and agentic AI solutions for end clients. This is a client-facing technical delivery role focused on applied AI/ML implementation, not sales. The right candidate will have strong Google Cloud experience, hands-on Gemini Enterprise or Google Cloud generative AI implementation experience, and the ability to translate client workflows into secure, scalable, production-ready AI solutions. This person should be comfortable moving between architecture, coding, prototyping, configuration, integration, and client-facing technical delivery. Responsibilities • Design, build, configure, and implement Gemini Enterprise solutions for end clients. • Develop AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows. • Build prototypes and proofs of concept that can be iterated into production-ready solutions. • Design and implement applied AI/ML solutions using Gemini Enterprise, Vertex AI, and related Google Cloud AI services. • Build and deploy LLM-powered applications, AI agents, retrieval-augmented generation workflows, and enterprise AI integrations. • Evaluate model options, agent patterns, grounding strategies, retrieval approaches, and integration paths based on client use cases. • Configure and deploy Gemini Enterprise agents, integrations, and related Google Cloud AI services. • Integrate AI agents with enterprise systems, data sources, APIs, and business applications. • Lead technical discovery with clients and translate requirements into solution architecture and implementation plans. • Develop scripts, connectors, workflows, or lightweight applications needed to support AI agent implementation. • Support model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness. • Apply best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment. • Communicate technical recommendations clearly to client engineering, data, security, cloud, and business stakeholders. Qualifications • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related field; equivalent practical experience will also be considered. • 5+ years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or hands-on client-facing technical delivery. • 3+ years of experience working with Google Cloud Platform. • Hands-on experience implementing Gemini Enterprise or Google Cloud generative AI solutions. • Hands-on experience designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or related tools. • Experience building, configuring, deploying, or integrating AI agents, generative AI applications, LLM-powered applications, or enterprise AI workflows. • Experience building agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or related agent development tools. • Experience with core agentic AI implementation patterns such as retrieval-augmented generation, prompt engineering, tool use/function calling, API integrations, enterprise system integration, and/or multi-agent workflows. • Experience with LLM application development, embeddings, model evaluation, prompt optimization, and production AI/ML implementation patterns. • Strong understanding of Google Cloud AI and data services, such as Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services. • Ability to code, script, prototype, and troubleshoot technical solutions in client environments. • Experience working directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions. • Strong understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices. • Excellent communication skills with the ability to explain complex technical concepts clearly. • Must be a U.S. Citizen or Green Card holder. Preferred Skills • Google Cloud Generative AI Leader certification. • Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification. • Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands-on implementation architect. • Experience with Python, JavaScript, TypeScript, or similar programming languages. • Experience with data integration, workflow automation, enterprise applications, embeddings, vector search, semantic search, model grounding, enterprise search, or retrieval-augmented generation pipelines. • Experience in consulting, systems integration, professional services, or client-facing technical delivery. • Familiarity with infrastructure as code, CI/CD, containers, serverless architecture, and cloud-native application deployment. Additional Information This position is open to direct candidates only. We are not working with third-party agencies, subcontractors, or C2C arrangements for this role. Candidates must be U.S. Citizens or Green Card holders.

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