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Open nowPosted 88 days ago

AIS Engineer

am5327 open roles

Where
São Paulo, SP, BR, Remote
Work mode
Remote
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Your applicationOpen nowAIS Engineeram53 · São Paulo, SP, BR, Remote

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on am53's own form.

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 88 days ago

The posting

Buscamos uma pessoa sênior em AI Engineering, com experiência prática em Google Cloud, Vertex AI, Gemini e soluções de Agentic AI. Essa pessoa atuará diretamente com clientes enterprise no desenho, implementação e evolução de soluções de IA e GenAI em produção. A posição exige interação frequente com clientes e equipes multinacionais da América Latina. Perfis com inglês ou espanhol apenas intermediário ou avançado não devem ser priorizados.

Principais responsabilidades:

Atuar diretamente com clientes enterprise na identificação de necessidades e definição das soluções técnicas. Conduzir workshops técnicos e discovery sessions. Participar da definição de arquiteturas e de decisões técnicas. Desenhar, desenvolver e evoluir soluções de IA e GenAI em produção utilizando o ecossistema Google Cloud. Construir arquiteturas de agentes e sistemas multiagentes. Implementar soluções de RAG, recuperação de informações e integração com bancos vetoriais. Desenvolver e operar pipelines completos de Machine Learning, incluindo treinamento, deploy, monitoramento, governança, avaliação e retraining. Implementar observabilidade, segurança, validação de respostas e mecanismos de proteção para aplicações de IA. Integrar soluções de IA com serviços cloud, APIs, plataformas de dados e ambientes corporativos complexos.

Requisitos obrigatórios

Experiência e atuação

Perfil sênior, com experiência prática e comprovada em Google Cloud Platform, GCP. Mínimo de 5 anos de experiência atuando diretamente com clientes enterprise. Experiência em ambientes corporativos complexos e regulamentados. Vivência na condução de workshops, discovery sessions, definição de arquiteturas e tomada de decisões técnicas. Experiência em projetos reais de IA, preferencialmente com soluções em produção. Não serão considerados perfis com experiência exclusivamente em AWS ou Azure.

Programação

Python obrigatório. Conhecimentos em Java, Go ou C++ serão considerados complementares.

Google Cloud, Vertex AI e MLOps

Experiência prática com:

Vertex AI e Gemini. AutoML. Vertex Pipelines e Vertex Experiments. Model Registry e Feature Store. Model Monitoring. Avaliação e retraining de modelos. Ciclo completo de Machine Learning, desde treinamento e deploy até governança e operação em produção.

Agentic AI e arquiteturas de agentes

Experiência comprovada com:

LangGraph. CrewAI. Google ADK, Agent Development Kit. MCP, Model Context Protocol. A2A, Agent-to-Agent. Function Calling e Tool Calling. Dynamic Routing. ReAct Pattern. Self Reflection. Hierarchical Delegation. Sistemas multiagentes.

RAG, dados e bancos vetoriais

Experiência prática com:

RAG, Retrieval-Augmented Generation. Agent Search e Agent Retrieval. BigQuery. Cloud SQL e AlloyDB. Bancos vetoriais modernos, como Pinecone, Weaviate, Qdrant ou pgvector. SQL e NoSQL. Construção de data pipelines. Processamento de dados em larga escala.

Integração e plataforma cloud

Experiência com:

Cloud Run. GKE. REST APIs. gRPC. SSE. Apigee. IAM. VPC Service Controls, VPC-SC.

Conhecimentos desejáveis

Observabilidade e LLMOps

Langfuse. AgentOps. Tracing de agentes. Monitoramento de workflows. Acompanhamento de custos de inferência, latência, consumo de tokens e métricas dos modelos.

Segurança aplicada à IA

Experiência com:

Prompt Injection Protection. Jailbreak Protection. PII Protection. Prevenção de vazamento de dados sensíveis. Guardrails. Output Validation. Hallucination Detection. Model Armor.

Plataformas de dados

Cloud Spanner. Cloud Bigtable. Firestore

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