Staff Software Engineer - Frameworks

BrazilRemoteFull-timelead

Software EngineerSoftware Engineering

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Quick Summary

Overview

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Software Engineer – Frameworks based in Brazil.

Technical Tools

Software EngineerSoftware Engineering

The Staff Software Engineer will play a leading role in shaping the architecture and technical execution of large-scale, mission-critical systems. You will tackle complex engineering challenges involving high-volume distributed systems, microservices orchestration, real-time machine learning, and low-latency conversational experiences. Working within a remote-first engineering organization, you will help drive an AI-first technology strategy and build resilient, scalable platforms for the future. The role requires strong technical judgment, architectural depth, and the ability to influence engineering practices beyond individual teams. You will collaborate with experienced engineers and cross-functional stakeholders to solve high-impact problems, improve system performance, and strengthen technical standards. This is an opportunity to combine hands-on engineering expertise with strategic leadership and long-term technical vision.

Lead the design and delivery of high-volume, high-concurrency, mission-critical distributed systems.
Define and evolve scalable software architectures that support complex business requirements and long-term technical growth.
Address challenging engineering problems involving distributed data consistency, fault tolerance, system resilience, and performance optimization.
Design architectures capable of supporting data-intensive applications, machine learning capabilities, and AI-powered product experiences at scale.
Contribute to the development of low-latency conversational journeys, microservices orchestration, and real-time machine learning processing.
Evaluate architectural and engineering trade-offs, balancing simplicity, flexibility, delivery speed, reliability, and build-versus-buy decisions.
Drive technical execution across engineering teams, helping establish high standards for software quality, system design, and maintainability.
Identify and remove collaboration barriers, facilitate difficult structural discussions, and promote effective decision-making across teams.
Foster an inclusive engineering culture through technical leadership, knowledge sharing, and constructive collaboration.
Support the evolution of existing systems, including opportunities to modernize legacy architectures and adopt more decoupled, event-driven approaches.
Apply AI-assisted engineering tools and practices to improve development workflows and technical productivity.

Requirements

~2 min read

10+ years of experience in software development, including leadership in delivering high-volume, high-concurrency, mission-critical distributed systems.
Deep knowledge of modern software architecture principles and distributed systems design.
Strong understanding of distributed data consistency, fault tolerance, system resilience, and performance optimization.
Experience designing and building data-intensive applications, with the ability to develop architectures that support machine learning and AI features at scale.
Proven ability to assess, explain, and make sound engineering trade-offs, including simplicity versus flexibility, delivery speed versus reliability, and build versus buy.
Demonstrated technical leadership and the ability to influence engineering decisions across teams.
Strong communication and collaboration skills, including the ability to resolve structural challenges, remove organizational barriers, and encourage an inclusive working environment.
Fluency in Portuguese and excellent English proficiency; both are mandatory.
Adaptability and strong problem-solving skills, with the ability to work across different technologies and engineering environments.

Nice to have:

Experience designing architectures that integrate large language models (LLMs), multi-agent AI systems, or complex data pipelines.
Strong knowledge of FinOps practices and cloud cost optimization in high-throughput environments.
Experience modernizing legacy monolithic systems into decoupled, event-driven architectures.
Familiarity with technologies such as Java, Kotlin, Node.js, Go, Python, React, and AWS is beneficial, although expertise in the entire technology stack is not required.
Experience using AI-assisted development tools such as Claude Code.