Sr. Platform Engineer

BrazilRemoteFull-timesenior

EngineeringDevops Engineer

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Quick Summary

Requirements Summary

Bachelor’s degree in Computer Science or a related technical field. 7+ years of relevant professional experience in software, data, platform, or infrastructure engineering.

Technical Tools

EngineeringDevops Engineer

This senior engineering role focuses on building the data infrastructure, automation, and distributed systems that support advanced machine learning products.
You will work with large-scale data pipelines and production systems designed to process massive volumes of events reliably and efficiently.
The position combines cloud infrastructure, software engineering, data engineering, and platform automation across technologies such as AWS, Python, Golang, Kafka, and Airflow.
You’ll collaborate closely with Data Scientists, Product Managers, and engineers to develop internal and external-facing services.
The role also emphasizes scalable infrastructure, CI/CD, container orchestration, and the practical use of AI to improve workflows and decision-making.
Working in a remote environment, you’ll have meaningful ownership over systems that enable teams to build, deploy, and operate data-driven solutions at scale.

Design and build scalable services and infrastructure that support machine learning and data-intensive products.
Develop automation tools and pipelines that enable Data Scientists and engineering teams to deploy, train, and evaluate models efficiently.
Build, maintain, and continuously improve production data systems capable of handling very large volumes of events.
Develop automated and scalable infrastructure and data pipelines with reliability, performance, and maintainability in mind.
Apply distributed systems principles and make appropriate architectural trade-offs when designing large-scale solutions.
Implement and maintain CI/CD practices that support reliable software delivery and operational excellence.
Work with cloud infrastructure, containerized environments, and orchestration technologies to support production workloads.
Collaborate with Product Managers, Data Scientists, and engineers across teams to deliver services supporting different aspects of machine learning data.
Participate in code reviews, pull requests, and engineering discussions to maintain high standards of software quality.
Leverage AI technologies to enhance decision-making, streamline workflows, improve operational efficiency, and support business outcomes.
Contribute to the continuous improvement of data engineering practices, infrastructure, automation, and platform capabilities.

Requirements

~2 min read

Bachelor’s degree in Computer Science or a related technical field.
7+ years of relevant professional experience in software, data, platform, or infrastructure engineering.
Strong knowledge of several relevant technologies, such as AWS, Python, Golang, Kafka, Airflow, Docker, Linux, and Kubernetes.
Proven experience working with very large volumes of data and building systems capable of operating at significant scale.
Strong understanding of distributed systems architecture and the trade-offs involved in designing scalable services.
Solid knowledge of CI/CD principles and software delivery best practices.
Practical experience with Docker and/or Kubernetes-based development and orchestration.
Proven experience using AI technologies to improve decision-making, streamline workflows and processes, increase efficiency, and drive business outcomes.
Experience creating automated and scalable infrastructure or pipelines for engineering, data, or scientific teams is highly valuable.
Familiarity with relational databases, key-value stores, or Kubernetes-based environments is beneficial.
Experience with Big Data technologies such as Apache Spark is a plus.
Familiarity with AWS services such as Batch, EMR, Glue, or SageMaker is advantageous.
Contributions to open-source communities through platforms such as GitHub, Stack Overflow, technical writing, or blogging are a plus.
Previous experience in cybersecurity, intelligence, or related technical domains is beneficial.
Strong collaboration and communication skills, with the ability to work effectively across multiple technical teams.