Databricks AI Architect

Invillia

. Define scalable data architectures using the Lakehouse paradigm .

Posted 9/22/2026full-timeSão Paulo • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining scalable data architectures using the Lakehouse paradigm and designing Databricks solutions for data ingestion, processing, and storage. Proficient in Machine Learning and Generative AI architectures, with a strong focus on data governance, security, and quality.

Highest-signal resume keywords

Lakehouse Architecture DefinitionDatabricks Solutions DesignMachine Learning ArchitectureModel Training and Deployment PipelinesVectorization and Semantic Search

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureData ModelingData GovernanceData SecurityData QualityAPI IntegrationScalabilityPerformance OptimizationObservabilityRetrieval-Augmented Generation (RAG)

Soft Skills

Technical LeadershipTeam Support

Tools & Technologies

DatabricksVector DatabasesVirtual AssistantsIntelligent AgentsEnterprise Copilots

Industry Keywords

Data IngestionData ProcessingData StorageEnterprise Systems IntegrationMachine Learning

About the role

Key responsibilities & impact

Define scalable data architectures using the Lakehouse paradigm
Design and specify Databricks solutions for data ingestion, processing, storage, and consumption
Establish standards for data modeling, governance, security, and quality
Define integration strategies with enterprise systems, APIs, and external platforms
Ensure the scalability, performance, and observability of implemented solutions
Lead technical reviews and support engineering teams in implementing solutions
Define architectures for Machine Learning and Generative AI solutions
Design and implement model training, evaluation, and deployment pipelines
Structure solutions based on RAG (Retrieval-Augmented Generation)
Define strategies for vectorization, semantic search, and the use of vector databases
Support the development and evolution of virtual assistants, intelligent agents, and enterprise copilots

Requirements

What you’ll need

Experience defining scalable data architectures using the Lakehouse paradigm
Knowledge of Databricks for data ingestion, processing, storage, and consumption
Knowledge of data modeling, governance, security, and quality
Experience integrating enterprise systems, APIs, and external platforms
Knowledge of scalability, performance, and observability for data solutions
Ability to lead technical reviews and support engineering teams
Knowledge of Machine Learning and Generative AI architectures
Experience building model training, evaluation, and deployment pipelines
Knowledge of solutions based on RAG (Retrieval-Augmented Generation)
Knowledge of vectorization, semantic search, and vector databases
Experience with virtual assistants, intelligent agents, and enterprise copilots

Benefits

Comp & perks

Position also open to candidates with disabilities
Hybrid work in Guarulhos – 2 days per week