Senior AI Platform Engineer

Role overview Build and evolve the cloud-native platform that enables engineering and data science teams to develop, operate, and scale machine-learning and AI systems. This senior role sits at the intersection of software engineering, infrastructure, and ML lifecycle orchestration, with a focus on making shared capabilities reliable and easy for distributed teams to use. It is remote within Brazil and open to candidates based there.

Responsibilities - Operate and extend infrastructure for Kubeflow, Feast, and Spark on Kubernetes as ML and AI workloads grow. - Create internal tools, APIs, and reusable abstractions that let teams manage more of their own development and deployment lifecycle. - Help data science teams apply engineering practices such as CI/CD, versioning, and testing to machine-learning workflows. - Improve orchestration from experimentation through production, including deployment automation and lifecycle practices for both MLOps and LLMOps. - Work with infrastructure and data teams to integrate ML artifacts with data catalog, privacy, and governance frameworks. - Gather developer feedback and use it to improve the platform experience while maintaining shared standards.

Requirements - Deep, hands-on experience with Kubeflow, Spark, Kubernetes, and AWS. - Strong Python skills for building reusable libraries, APIs, and developer tooling. - Experience applying DevOps practices to ML or AI systems, including CI/CD, infrastructure as code, and observability. - Ability to partner with data science teams to design platform capabilities and support their adoption. - Systems-level thinking about how ML infrastructure connects to data catalogs, privacy, and governance. - A product-oriented approach to internal platforms, with attention to developer experience and practical, production-ready solutions.

Benefits and work setup The role is remote within Brazil, with flexible work arrangements and schedules and a home-office reimbursement. Listed benefits include health, dental, and life insurance; wellness and emotional-support resources; paid parental leave; and paid time off that grows with tenure, plus a birthday day off. Career-development and learning resources are also available.