---
title: 'Open Application at Avra'
canonical: 'https://feeny.ai/job/open-application-avra-sao-paulo-t9a0zay6e7qs'
type: 'job'
last_seen: '2026-09-12'
---

# Open Application at Avra

- **Company:** Avra
- **Location:** São Paulo, Brazil
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-05-22
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/avra/f9cf3287-1016-49cd-b1a1-1e3dec4c91ec

## Job description

We are always looking for exceptional candidates to join our team. If none of our open roles are a match, get in touch anyway. And tell us what you'd do here.

## About Avra

## Company Overview
- **One-liner**: Avra is a frontier AI lab building a predictive platform for enterprise decisions, powered by a Graph Foundation Model that models the relational economy.
- **Entity Type**: Private (early-stage startup)
- **Headquarters**: São Paulo, Brazil
- **Founded**: 2024
- **Founders**: Bruno Alano (CEO, co-founder) and Viviane Meister (CTO, co-founder)

## Core Business
- **Primary industry**: Enterprise AI / Decision Intelligence (credit, fraud, growth, monitoring)
- **Target customers**: B2B, Enterprise (banks, fintechs, marketplaces, SMB lenders)
- **Mission**: “Model relationships over time. Improve the decision systems enterprises already run.”

## Products & Services
- **Avra Graph Foundation Model**: A pre-trained temporal knowledge graph covering Brazil’s economy – companies, individuals, events, ownership, judicial events, geography. Fine-tuned per customer workspace for credit scoring, fraud detection, and propensity modeling.
- **Avra API & SDK**: Managed endpoints (mTLS) for prediction and explanation, with tenant isolation and audit trails.
- **Avra Playground**: Browser-based environment to experiment with decision flows, replay traffic, and inspect evidence.
- **Enterprise Deployment**: Shadow deployments alongside incumbent models, with batch and real-time inference surfaces.

## Market Standing
- **Valuation / Market Cap**: Not publicly available
- **Key Metric**: Total funding amount not disclosed; backed by “frontier funds across two continents”
- **Notable Investors/Partners**: Not named explicitly, but investors are described as “frontier funds across two continents”. Team alumni include OpenAI, Stone, Itaú, McKinsey, Embraer, XP, HSBC, Santander.
- **Growth Signals**: Small team (~20 people) with 7 open roles; remote-first with HQ in São Paulo; pilot results showing 1.8× NII on Avra-scored cohort, +90% conversion lift, +5.4 p.p. ROC AUC on held-out test set.

## Competitive Advantages
- **Graph-native reasoning**: Models relationships over time rather than flat rows, capturing risk dimensions orthogonal to traditional features (18–22% correlation with existing features).
- **Inductive generalization**: Scores entities never seen before by reasoning through counterparties and graph position.
- **Brazil-native foundation**: Trained on local semantics (CNPJs, corporate groups, informal networks) and legal events.
- **Developer-first, enterprise-ready**: API, SDK, playground, tenant isolation, ISO 27001 in progress, LGPD compliant.

## Strategic Focus
- Expand the Graph Foundation Model platform across more enterprise decision use cases (credit, fraud, growth, monitoring).
- Grow the team (~20 today) with research scientists, data engineers, and deployment strategists.
- Maintain a “small on purpose” approach with deep stack ownership from data ingest to live decision.

## Why Work Here
- **Culture**: “Small team, deep stack, real ownership.” Engineers, scientists, and operators own the work end-to-end.
- **Remote / Hybrid**: Remote-first with hybrid options in São Paulo.
- **Team Background**: Colleagues from OpenAI, Stone, Itaú, McKinsey, Embraer, XP, HSBC, Santander.
- **Perks**: Frontier research that ships into production; publish-grade research with real business impact; no contractors on the model path.
- **Open Roles**: 7 positions including Research Scientist, Senior Data Engineer, Staff Software Engineer, Deployment Strategist, Marketing Lead, Enterprise Sales.

## Sources
1. [avra.ai/about](https://avra.ai/about)
2. [avra.ai/careers](https://avra.ai/careers)
3. [avra.ai](https://avra.ai/?r=0)
4. [avra.ai/en/about](https://avra.ai/en/about)
5. [jobs.ashbyhq.com/avra](https://jobs.ashbyhq.com/avra)

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