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Senior Software Engineer - Data Platform

Roles & Responsibilities

  • 5+ years of experience building and operating production software systems.
  • Strong backend engineering experience with Go, Python, Rust, or similar languages.
  • Demonstrated ability to take ownership of ambiguous problems and drive initiatives.
  • Strong analytical and debugging skills.

Requirements:

  • Design, build, and maintain the core services that power Avra’s data platform.
  • Develop and operate distributed systems connecting data, infrastructure, and product experiences.
  • Design systems that ingest, process, and operationalize real-world data.
  • Continuously improve the platform by reducing operational complexity and increasing developer productivity.

Job description

About Avra

Avra is building relational foundation models for enterprise decision-making in Brazil.

Our work focuses on graph-native models for structured, high-stakes prediction problems: credit, fraud, growth, monitoring, and other decisions where entities cannot be understood in isolation. We model companies, people, and the relationships between them as evolving networks, then adapt those representations to customer-specific prediction tasks that plug into existing decisioning systems.

We work with internationally recognized research advisors, and we care about research that becomes useful in production. Our systems are already in production with large enterprise customers, supporting high-volume workflows where reliability, latency, model quality, and operational safety all matter.

The Role

Behind Avra's Foundation AI sits a critical layer: a data platform that ingests, structures, and operationalizes messy, real-world data into reliable inputs for our models and products.
As a Senior Software Engineer on the Data Platform team, you’ll play a key role in building and operating the systems that power Avra’s AI infrastructure. You’ll work across the entire stack, designing and developing data products, APIs, customer-facing workspaces, streaming data systems, deployment pipelines, and the core services that connect them all.

This is a highly cross-functional role with significant ownership. You’ll collaborate closely with product, research, and product engineering teams to transform complex data challenges into scalable, reliable systems that directly impact our customers and our models.

 

Responsibilities

  • Data Products & Platform Services. Design, build, and maintain the core services that power Avra’s data platform, including APIs, customer-facing workspaces, ingestion systems, and internal tooling used across the company.

  • Distributed Systems & Integrations. Develop and operate distributed systems that connect data, infrastructure, and product experiences. Build reliable integrations between internal services, third-party systems, and AI-powered applications.

  • Real-World Data Processing. Design systems that ingest, process, and operationalize messy, incomplete, and evolving real-world data. Handle schema evolution, edge cases, operational failures, and data quality challenges with strong engineering judgment.

  • Cloud Infrastructure & Deployment. Work within cloud-native environments (GCP/AWS), building and operating services, deployment pipelines, messaging systems, storage layers, and infrastructure automation.

  • Developer Experience & Platform Improvement. Continuously improve the platform by reducing operational complexity, increasing developer productivity, strengthening observability, and simplifying system architecture.

  • Cross-Functional Collaboration. Partner closely with AI, Product, and Infrastructure teams to build platform capabilities that directly power customer-facing products and Foundation AI systems.

 

Qualifications

  • Experience - 5+ years of experience building and operating production software systems. Experience working on platform, backend, infrastructure, or data-intensive systems is highly valued.

  • Technical Proficiency -

    • Strong backend engineering experience with Go, Python, Rust, or similar languages

    • Strong understanding of distributed systems, APIs, cloud infrastructure, data-intensive applications, streaming and production reliability

  • Ownership - Demonstrated ability to take ownership of ambiguous problems, drive initiatives from design through production, and balance short-term delivery with long-term maintainability.

  • Problem Solving - Strong analytical and debugging skills with the ability to navigate complex systems, identify root causes, and deliver pragmatic solutions.

You Stand Out If

  • You have significant experience building, operating, and improving production software systems. You understand that reliability, observability, and maintainability matter as much as shipping new features.

  • You enjoy working across multiple domains, from backend services and APIs to data systems and infrastructure. You can quickly navigate unfamiliar systems and contribute wherever the business needs you most.

  • You write clean, maintainable code, perform thoughtful code reviews, and consistently raise the engineering quality bar for the teams around you.

  • Experience with cloud platforms (GCP or AWS), event-driven architectures, streaming systems, APIs, distributed systems, CI/CD pipelines, infrastructure automation, or large-scale data platforms is highly valued.

  • Experience building systems that support machine learning, AI products, data processing workloads, or large-scale data infrastructure is a strong advantage.

What We Offer

  • Competitive Compensation - Attractive salary and equity participation

  • Ownership & Impact - Direct influence on the foundation of Avra’s data platform and its evolution

  • Technical Environment - Work on real-world data problems involving complex ingestion, reliability, and large-scale systems

  • Lean, High-Quality Team - Work closely with experienced engineers and founders in a high-context environment

  • Flexible Culture - Remote-first (Brazil), with flexible time off and a strong focus on autonomy

If you’re excited about building production systems, solving difficult engineering problems, and creating the infrastructure that powers next-generation AI products, we’d love to hear from you.

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