Informação geral

Sol. nº:
WD00084092
Área de carreira:
Engenharia de Hardware
País/Região:
Brasil
Estado:
São Paulo
Cidade:
JAGUARIUNA
Data:
Quarta, Julho 2, 2025
Horário de trabalho:
Full-time
Locais Adicionais: 
* Brazil - São Paulo - Jaguariúna
* Brazil - São Paulo - JAGUARIUNA

Por que trabalhar na Lenovo

Nós somos a Lenovo. Fazemos o que dizemos. Somos responsaveis pelo que fazemos. Nós deslumbramos os nossos clientes.

A Lenovo é uma potência tecnológica global, ranqueada em 248º lugar na Fortune Global 500, com receita de US$ 57 bilhões e servindo milhões de clientes em 180 mercardos diferentes todos os dias. Focada em uma visão ousada para fornecer uma tecnologia mais inteligente para todos, a Lenovo construiu seu sucesso como a maior empresa de PC do mundo,  com um portfólio completo de dispositivos habilitados por IA, prontos para IA e otimizados para IA (PCs, estações de trabalho, smartphones, tablets), infraestrutura (servidor, armazenamento, edge, computação de alto desempenho e infraestrutura definida por software), software, soluções e serviços. O contínuo investimento da Lenovo em inovação que muda o mundo está construindo um futuro mais equitativo, confiável e inteligente para todos, em qualquer lugar. A Lenovo está cotada na bolsa de valores de Hong Kong sob a designação Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

Para saber mais, visite lenovo.com, e leia sobre as últimas notícias através do nosso StoryHub

Descrição e requisitos

Scope of Responsibilities
  • Lead the design, development, and deployment of scalable, cloud-native applications and services across multiple environments.

  • Architect and implement complex cloud infrastructure solutions using Infrastructure-as-Code (IaC) tools such as Terraform, AWS CloudFormation, or equivalent, ensuring security, scalability, and cost efficiency.

  • Own and optimize CI/CD pipelines, and establish best practices for automation, testing, and deployment for distributed engineering teams.

  • Design, develop, and expose robust APIs and endpoints to enable integration with advanced AI/ML platforms such as Google Vertex AI, OpenAI, and AWS SageMaker for high-performance inference workflows.

  • Monitor and enhance application performance, reliability, and security in production cloud environments; proactively troubleshoot and resolve complex issues.

  • Provide technical leadership and mentorship to junior and mid-level developers; perform in-depth code reviews and promote engineering best practices and clean architecture principles.

  • Drive documentation and knowledge sharing related to cloud architecture, operational excellence, and emerging cloud-native technologies.

  • Collaborate cross-functionally with product owners, architects, and stakeholders, contributing to strategic technical decisions and long-term cloud roadmaps.

  • Stay ahead of industry trends in cloud computing, AI/ML workflows, serverless architectures, container orchestration (Kubernetes, Docker), and help drive the adoption of new tools and approaches within the team.

Basic Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field — or equivalent practical experience.

  • 5+ years of professional experience in designing and building production-grade cloud-native applications.

  • Proven expertise with at least one major cloud provider (e.g., AWS, Google Cloud Platform, Azure) and deep understanding of its ecosystem.

  • Strong hands-on experience architecting and deploying RESTful APIs and scalable microservices.

  • Demonstrated experience building and managing Infrastructure-as-Code (Terraform, CloudFormation, or similar).

  • Advanced programming proficiency in modern languages such as Python, TypeScript/JavaScript, Go, or Java.

  • Strong knowledge of containerization and orchestration technologies (Docker, Kubernetes) in production environments.

  • Practical experience integrating or deploying AI/ML models in cloud workflows (e.g., Vertex AI, OpenAI, SageMaker).

  • Solid understanding of CI/CD concepts and automation tools.

  • Excellent problem-solving, debugging, and system optimization skills.

  • Effective communicator with experience working in Agile environments.


Preferred Qualifications
  • Prior experience in a technical leadership role, guiding engineers through complex design decisions, architecture reviews, and code quality standards.

  • Mentorship experience, helping to upskill junior team members and foster a culture of knowledge sharing.

  • Cloud certification at the professional or specialty level, such as:

    • AWS Certified Solutions Architect — Professional

    • Google Professional Cloud Architect

    • Microsoft Azure Solutions Architect Expert

  • Hands-on experience integrating AI/ML solutions at scale, particularly for real-time inference or large-scale data pipelines.

  • Familiarity with DevSecOps practices and secure cloud architectures.

  • Excellent collaboration skills with cross-functional and geographically distributed teams.
#MBG

Locais Adicionais: 
* Brazil - São Paulo - Jaguariúna
* Brazil - São Paulo - JAGUARIUNA
* Brazil - São Paulo - Jaguariúna , * Brazil - São Paulo - JAGUARIUNA
* Brazil - São Paulo
* Brazil
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