Google Cloud AI Solutions Architect, Gemini Enterprise

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, configure, and implement Gemini Enterprise solutions for end users.

• Create AI agent workflows that facilitate business use cases, internal processes, enterprise automation, and operational workflows.

• Construct prototypes and proofs of concept that can be refined into production-ready solutions.

• Design and implement applied AI/ML solutions utilizing Gemini Enterprise, Vertex AI, and other Google Cloud AI services.

• Develop and deploy LLM-powered applications, AI agents, retrieval-augmented generation workflows, and enterprise AI integrations.

• Assess model options, agent patterns, grounding strategies, retrieval methods, and integration paths according to client use cases.

• Configure and deploy Gemini Enterprise agents, integrations, and associated Google Cloud AI services.

• Connect AI agents with enterprise systems, data sources, APIs, and business applications.

• Lead technical discovery sessions with clients and convert requirements into solution architecture and implementation strategies.

• Create scripts, connectors, workflows, or lightweight applications necessary for AI agent implementation.

• Assist with model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness.

• Implement best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment.

• Clearly communicate technical recommendations to client engineering, data, security, cloud, and business stakeholders.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related discipline; equivalent practical experience will also be accepted.

• Over 5 years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or direct client-facing technical delivery.

• More than 3 years of experience working with Google Cloud Platform.

• Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.

• Practical experience in implementing Gemini Enterprise or Google Cloud generative AI solutions.

• Direct experience in designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or similar tools.

• Experience in building, configuring, deploying, or integrating AI agents, generative AI applications, LLM-powered applications, or enterprise AI workflows.

• Familiarity with developing agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or comparable agent development tools.

• Knowledge of 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, including Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services.

• Capability to code, script, prototype, and troubleshoot technical solutions in client environments.

• Experience collaborating directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions.

• In-depth understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices.

• Exceptional communication skills with the ability to articulate complex technical concepts clearly.

🏝️ Benefits

• Must be a U.S. Citizen