Google Cloud AI Solutions Architect, Gemini Enterprise

🕒 il y a 1 mois

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

💻 Ingénieur Solutions

👻 Score fantôme 25%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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The Data Sherpas

Site WebLinkedInTous les Emplois

11 - 50 employés

Fondée en 2010

💼 Conseil

🤖 Intelligence artificielle

📣 Marketing

Consulting • Artificial Intelligence • Marketing

The Data Sherpas est une entreprise de services de données et d'analytique, indépendante de toute plateforme, qui aide les organisations à adopter des solutions d'IA, de cloud, de martech et d'adtech. Axée sur l'innovation, elle fournit des services de conseil et des services gérés pour renforcer les entreprises grâce à des capacités avancées en matière de données, d'IA et de cloud, afin de faciliter la prise de décisions stratégiques, d'améliorer l'efficacité opérationnelle et de procurer un avantage concurrentiel. Son site web met en avant des études de cas, des partenariats de marque et des services couvrant les données, l'IA, le cloud, le martech et l'adtech.

Description

• 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.

🎯 Exigences

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

🏖️ Avantages

• Must be a U.S. Citizen