Sr. Platform Engineer

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• 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:

• 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.

Benefits:

• Fully remote work opportunity in Brazil.
• Full-time employment.
• Competitive compensation and equity opportunities.
• Comprehensive physical and mental wellbeing programs.
• Competitive vacation and paid time-off policies.
• Paid parental and adoption leave.
• Professional development opportunities available across different levels and roles.
• Employee networks, geographic community groups, and volunteering opportunities.
• Opportunity to work on large-scale data infrastructure, distributed systems, cloud technologies, and machine learning platforms.
• Collaboration with Data Scientists, Product Managers, and engineers across multiple teams.
• Exposure to AI technologies and their practical application to engineering workflows and business outcomes.
• Opportunities to work with high-volume data systems, automation, Kubernetes, CI/CD, and modern cloud infrastructure.
• Specific salary figures and Brazil-specific healthcare details were not specified in the source job description.