Grupo QuintoAndar | Staff Software Engineer
Staff Software Engineer at Grupo QuintoAndar, Latin America's largest real-estate ecosystem. Remote-first across Brazil (São Paulo office optional), you'll drive high-impact distributed systems for the company's AI-first pivot — low-latency conversational journeys, microservices orchestration, real-time ML — using Java, Kotlin, Node.js, Go, Python, React on AWS.
- Compensation
- Not disclosed
- Location
- Brasil
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 10+ years of software development experience, leading delivery of high-volume, high-concurrency, mission-critical distributed systems
- Deep knowledge of modern software architecture paradigms, distributed data consistency, fault tolerance, and system optimization
- Understanding of data-intensive applications; readiness to build architectures supporting ML/AI features at scale
- Ability to analyze and articulate engineering trade-offs concretely (simplicity vs flexibility, velocity vs reliability, build vs buy)
- Capability to remove collaboration barriers, conduct difficult structural conversations, and foster inclusive engineering culture
- Fluency in Portuguese and excellent English skills (mandatory)
Nice to have
- Experience designing architectures that natively integrate with LLMs, multi-agent AI systems, or heavy data pipelines
- Strong background in FinOps and cost optimization for high-throughput cloud environments
- Experience migrating legacy monoliths into decoupled, event-driven architectures
Full description
About Grupo QuintoAndar
Grupo QuintoAndar is the largest real estate ecosystem in Latin America, with brands and solutions across six countries.
Our purpose is to help people love where they live by making the housing journey simpler, from finding a home to managing life in it.
We’re also investing R$ 2 billion in technology and AI over the next two years, expanding our engineering capabilities and developing more conversational product experiences. To learn more about our story, visit:.
Location & Remote Work
Our technology team operates under a "remote-first" model, which means we work from home and can live anywhere in Brazil. We also offer the option of working from our São Paulo office. Furthermore, we offer the Work From Anywhere program, allowing you to work from any country for up to 90 days a year, ensuring you have the flexibility to do the best work of your career.
The Role
As a Staff Software Engineer, you will be a core driver of our technical execution. Here, you won't just "maintain old systems" or "take tickets." We are an organization of builders guided by deep technical density. You will use our Leadership Principles, like Dive Deep and Make it Great, to solve high-impact distribution problems and build the systems of our next decade.
We believe that technology scales execution, but senior talent scales judgment. You will be at the forefront of our AI-First pivot, designing highly scalable, resilient systems capable of supporting low-latency conversational journeys, heavy microservices orchestration, and real-time ML processing.
Our Tech Stack: We work with Java, Kotlin, Node.js, Go, Python, React, and more, primarily hosted on AWS. Our daily workflow also incorporates various AI tools, including Claude Code.
Don't worry if you haven't mastered our exact stack. We value strong problem-solving skills, adaptability, and an engineering mindset over specific technology experience.
Position & Technical Challenges:
We hire Staff Software Engineers through a unified selection process for multiple engineering teams.
At the final stage, you'll have the opportunity to explore which team best matches your experience and interests, alongside our hiring needs.
What we are looking for:
- 10+ years of experience in software development, leading the delivery of high-volume, high-concurrency, and mission-critical distributed systems.
- Deep knowledge of modern software architecture paradigms, distributed data consistency, fault tolerance, and system optimization.
- Understanding of data-intensive applications and readiness to build architectures that support Machine Learning/AI features at scale.