---
title: 'Member of Technical Staff | Observability & Reliability at Avra'
canonical: 'https://feeny.ai/job/member-of-technical-staff-observability-reliability-avra-sao-paulo-zdz2h5v0qkq2'
type: 'job'
last_seen: '2026-09-26'
---

# Member of Technical Staff | Observability & Reliability at Avra

- **Company:** Avra
- **Location:** São Paulo, Brazil
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-09-23
- **Last confirmed live:** 2026-09-26
- **Apply:** https://jobs.ashbyhq.com/avra/d38b99c8-fc77-4c87-9fe1-2375f424b39b

## Job description

## About the role

At Avra, every technical IC is a Member of Technical Staff (MTS). The title doesn't put anyone in a silo: you own systems and outcomes, not steps in a function, and you keep building depth in your area. In this role, you'll join the Platform team as our go-to expert on observability and reliability. Our customers make real-time decisions based on our responses, so when we're down, their operations stop. Avra's cloud is just one more dataplane, alongside the dataplanes we operate inside customer environments — so observability and reliability have to work the same way everywhere.

## What you'll do

- Evolve our observability stack for logs, metrics, traces, and alerting.
- Make sure every dataplane, in our cloud and on-premise, reports its active release, health, heartbeat, logs, metrics, and usage to the control plane.
- Bring telemetry into customer clusters within a model where agents only make outbound connections.
- Detect drift between the desired state and what's actually running in each environment.
- Monitor the health of our deployment and runtime agents.
- Provide visibility into ephemeral workloads, such as the Ray clusters that run our batch inference.
- Define SLOs, lead incident response and postmortems, and reduce MTTR — including when a fix requires coordinating with the customer.
- Reduce telemetry cost: less redundant data, more useful signal.

## How we measure success

- 99.9% serving availability, with incidents trending down.
- MTTR, including on-premise incidents.
- Near-zero drift between desired and actual state.
- All agents active and reporting, across every dataplane.

## What we're looking for

- Deep experience with OpenTelemetry and observability backends.
- Hands-on practice with SLOs, error budgets, actionable alerting, and incident management.
- Strong experience with Kubernetes and infrastructure as code (Terraform / Helm ).
- Experience operating software in environments you don't fully control.
- Production-quality code and reviews, and a willingness to operate what you build.

## Nice to have

- Shipping software to customer-hosted Kubernetes (e.g., Helm, outbound-only connectivity).
- GCP or GKE, AWS or EKS.
- ML multi-node/multi-cluster workloads in production.
- Financial services or regulated environments.

## 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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