This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Pessoa Engenheira de Plataforma de IA Sênior based in Brazil.
This role is at the core of building and scaling a corporate AI platform designed to support modern, production-grade AI workloads. You will be responsible for architecting and evolving the underlying infrastructure that enables AI services, agents, APIs, and data pipelines to run securely and at scale. The position blends cloud engineering, Kubernetes expertise, automation, and platform reliability, with a strong focus on security, observability, and cost efficiency. You will work closely with AI, Data, Product, and Engineering teams to translate technical requirements into a robust and reusable platform. This is a highly strategic role where your decisions will directly impact scalability, developer experience, and operational excellence. The environment is fast-moving, collaborative, and centered on building reliable systems for critical AI-driven products.
Accountabilities:
- Design, build, and evolve cloud-native and Kubernetes-based environments for AI workloads, APIs, services, and data pipelines
- Develop and maintain CI/CD pipelines with strong focus on security, traceability, standardization, and deployment efficiency
- Implement Infrastructure as Code practices to automate provisioning and management of cloud resources
- Define and implement observability standards, including logging, metrics, tracing, alerting, and platform health monitoring
- Support AI workloads such as inference services, embeddings, agent orchestration, and model integration components
- Ensure robust security practices including identity and access management, secrets handling, and environment segregation
- Drive platform reliability through performance tuning, scalability improvements, resiliency, and cost optimization (FinOps)
- Create reusable architectural patterns for deployment, monitoring, infrastructure, and operational workflows
- Collaborate with AI, Data, Product, and Engineering teams to translate needs into scalable platform capabilities
Requirements:
- Strong hands-on experience with cloud platforms (AWS, Azure, or GCP)
- Solid experience with Kubernetes, containers (Docker), Helm, and cloud-managed services
- Proven experience with CI/CD tools such as GitHub Actions, GitLab CI, Azure DevOps, or Jenkins
- Strong knowledge of Infrastructure as Code tools such as Terraform, Pulumi, or CloudFormation
- Experience implementing observability solutions (logging, monitoring, tracing, dashboards, alerting)
- Solid understanding of networking, load balancing, authentication, authorization, and high availability architectures
- Experience operating production systems, handling incidents, and improving system reliability
- Ability to document technical standards, architecture decisions, and platform practices clearly
- Experience with MLOps/LLMOps, GPU workloads, or AI platforms is a strong plus
- Familiarity with tools such as vLLM, Triton, NVIDIA NIM, MLflow, Kubeflow, or Ray is a plus
- Knowledge of API gateways, service mesh, secrets management, and cloud security policies is a plus
- Understanding of FinOps and infrastructure cost optimization is a plus
- Experience in enterprise environments with governance, RBAC, and compliance requirements (e.g., LGPD) is a plus
Benefits:
- Flexible remote-first (“Anywhere Office”) work model
- Cooperative hiring model with structured collaboration environment
- Home office allowance via iFood Benefits (flexible spending balance)
- BYOD support for device acquisition or personal machine usage
- Wellness benefits including TotalPass, Wellhub access, and health partnerships
- Additional perks such as birthday day off and temporary disability insurance support
- Professional development support through trainings and certifications
- Discount and benefits club access (People Hub)
- Collaborative and innovation-driven culture focused on autonomy and ownership
- Opportunity to work on cutting-edge AI infrastructure and large-scale systems.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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