About Avra

Avra is a frontier AI lab building relational foundation models from the ground up (no third-party wrappers).

We model how businesses and individuals are connected and interact over time. Put simply: we bring connections into the math.

Leading enterprises in LatAm use Avra's models to power key decisions in credit, growth, and fraud. Our customers include the largest banks and marketplaces in Latin America, such as Mercado Libre, Telefonica, Banco Inter and Getnet.

Avra was founded in 2024 by Viviane Meister and Bruno Alano (ex-OpenAI). Our investors include NXTP, Clocktower Ventures, as well as the Sequoia and a16z scouts. We are accelerated by NVIDIA, AWS, and Google.

We are a team of builders. Join us.

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 to own what customers and operators touch. A model that exists but isn't available generates no revenue: the API, the dashboard, and batches are how a governed release becomes a product. You'll build those surfaces, with correct usage and billing, plus leverage other teams to delivery in the platform ecosystem building strong platform foundations.

What you'll do

• Evolve the API and the online and batch prediction APIs that enterprise customers integrate into their own systems.

• Evolve the dashboard and workspaces: Filetransfer, batches, models, test predictions, webhooks, and API keys.

• Build usage, quotas, and the billing integration, so every unit of consumption is metered, attributed to the right workspace, and billed correctly.

• Build the Avra Core foundations: enabling other teams to delivery data sources, corrections, schema, target, and horizon, all the way from model training and evaluations to the first prediction in production.

• Expose the catalog, versions, and status of models governed by ML Systems, without creating a second source of truth.

• Give Ops visibility into every run per customer: backoffice, notifications, and a production panel.

How we measure success

• Time from ML Systems authorizing a release to customers consuming it via API, dashboard, and batch.

• Correct usage and billing: every unit of consumption metered, attributed, and billed without errors.

• Surface quality: API error rate, dashboard bugs, and batch failures customers notice.
  

What we're looking for

• 7+ years of relevant engineering experience at tech and product-driven companies

• Experience building and running B2B products or public APIs in production, with customers who depend on them.

• Strong API design: versioning, idempotency, pagination, rate limiting, authentication, and keys.

• Experience with multi-tenant systems: organizations, workspaces, permissions, and isolation.

• Production code in Go and TypeScript, from backend to UI.

• Product sense: you work with Product and FDEs to understand the customer's problem before writing code.

• Production-quality code and reviews, and a willingness to operate what you build.

• Daily use of coding agents, with an opinion on how to use them safely.

Nice to have

• Usage-based metering and billing (Orb, Stripe, or similar).

• Webhooks and event delivery at scale (Svix or similar).

• Data or ML products: long-running jobs, large files, asynchronous status.

• Developer experience: SDKs, API documentation, self-service onboarding.

• Kubernetes and GCP.

• Financial services or regulated environments.