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Specialist AI Architect – Google Cloud Platform (GCP)
Rox Partner. Lead the definition of the enterprise Artificial Intelligence architecture .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining and implementing enterprise Artificial Intelligence architectures, with a strong focus on Google Cloud Platform services and best practices for AI solutions. Capable of leading technical discussions and integrating AI models with enterprise systems while ensuring data governance and security.
Highest-signal resume keywords
AI Architecture DefinitionGoogle Cloud Platform (GCP)Vertex AIGenerative AIMLOps
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Artificial IntelligenceMachine LearningPythonSQLAPI DevelopmentData GovernanceEvent-Driven ArchitecturesMicroservicesData QualityData Lineage
Soft Skills
Technical LeadershipBusiness TranslationInfluencing Strategic Decisions
Tools & Technologies
BigQueryCloud StorageDataflowPub/SubCloud ComposerCloud RunCloud FunctionsCloud SQLIAMLangChain
Certifications & Qualifications
Google Cloud Professional Cloud ArchitectProfessional Data EngineerProfessional Machine Learning Engineer
Industry Keywords
Generative AILLMsRAGPrompt EngineeringVector DatabasesTOGAF
Tech Stack
Tools & technologiesAirflowApacheBigQueryCloudERPGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Lead the definition of the enterprise Artificial Intelligence architecture
- Establish standards, frameworks, and best practices for AI, Generative AI, and Machine Learning solutions on GCP
- Design scalable architectures for LLMs, Generative AI, RAG, intelligent agents, and multimodal systems
- Define development, integration, deployment, monitoring, and governance standards for AI solutions
- Serve as a technical reference across business, Data Engineering, Data Science, Analytics, Software Engineering, and Technology teams
- Design virtual assistants, copilots, semantic search, intelligent automation, document processing, recommendation, classification, and summarization solutions
- Define integration strategies between AI models, data platforms, APIs, microservices, ERP, CRM, SAP, legacy systems, and business applications
- Lead architectures using Vertex AI, Gemini, and GCP AI services
- Design AI pipelines using MLOps, LLMOps, DataOps, CI/CD, and infrastructure as code
- Define strategies for the evaluation, monitoring, and continuous evolution of AI models
- Ensure security, privacy, data governance, and Responsible AI
- Support the evolution of the enterprise AI platform and evaluate new technologies
- Conduct As-Is and To-Be technical assessments
- Influence strategic decisions regarding the enterprise AI architecture
Requirements
What you’ll need- Extensive experience as an AI Architect, Solutions Architect, Data Architect, Principal Data Engineer, or Tech Lead on enterprise Artificial Intelligence projects
- Proven experience defining architectures using Google Cloud Platform (GCP)
- Strong knowledge of Vertex AI, Gemini, BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataplex, BigLake, Cloud Composer (Apache Airflow), Cloud Run, Cloud Functions, Cloud SQL, and IAM
- Experience with Generative AI, LLMs, intelligent agents, and conversational systems
- Knowledge of RAG, Prompt Engineering, Function Calling, Tool Use, embeddings, vector databases, and agentic AI architectures
- Experience with Vertex AI Agent Builder, Vertex AI Search, or equivalent solutions
- Experience with Machine Learning, MLOps, LLMOps, and the complete AI model lifecycle
- Experience with Python, SQL, and API development
- Knowledge of event-driven architectures, microservices, and integration across enterprise systems
- Knowledge of data governance, information security, observability, Data Quality, and Data Lineage
- Experience with Git, CI/CD, DevSecOps, and software engineering best practices
- Ability to lead technical discussions and translate business challenges into modern AI architectures
- Google Cloud Professional Cloud Architect, Professional Data Engineer, and/or Professional Machine Learning Engineer certifications are a plus
- Experience with LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks is a plus
- Knowledge of vector databases such as Vertex AI Vector Search, Pinecone, Weaviate, Milvus, FAISS, or PGVector is a plus
- Knowledge of TOGAF is a plus
Benefits
Comp & perks- iFood Benefits (meal and food allowance) — BRL 704.00 per month, cumulative
- Health Insurance — Unimed Apartment plan (optional)
- Life Insurance
- Birthday Day Off with a gift card
- Day off for every two articles approved and published on the Roxpert Blog
- Access to Hotmart, Alura, A Cloud Guru, O’Reilly, and RoxSchool platforms
- Reimbursement of up to BRL 300.00 per certification
- BRL 300.00 bonus for each certification earned, subject to prior alignment with the manager
- Psychological Support Allowance — up to two psychotherapy sessions per month
- Feedz — engagement, feedback, communication, recognition, and development platform
- Wellhub — access to gyms, studios, and health and wellness apps
- SESC partnership
- Work Equipment — all necessary equipment provided