Remote Engineering Lead – Credit Risk & ML Systems

Kiwi; Buenos Aires; Remote; ARS 212,899,000 - 273,727,000; Full time

Job summary

Kiwi is seeking a hands-on Engineering Lead to guide the Credit Risk Engineering team, building backend services and APIs that power our lending platform. You will collaborate closely with Credit Risk and Data Science to deploy validated models into production and to improve MLOps, reliability, and deployment practices.

You will mentor engineers, drive technical direction, and ensure scalable, observable systems across Cloud (AWS) and containerized environments.

Qualifications

• Experience leading engineers while remaining hands‑on with system design, implementation, and production support.
• Strong backend engineering experience with TypeScript and Node.js, including building and operating APIs and microservices.
• Experience integrating services into critical customer flows, with a solid understanding of latency, timeouts, partial failures, retries, and observability.
• Proven hands‑on experience with MLOps in production, including model deployment, versioning, monitoring, and rollback.
• Working knowledge of Python and experience collaborating on systems that serve machine learning models in production.
• Experience deploying and operating containerized services on AWS, using Docker and CI/CD pipelines.
• Strong SQL and PostgreSQL skills, including investigating data quality and production issues.
• Strong technical judgment and the ability to work effectively across Engineering, Credit Risk, and Data Science.

Responsibilities

• Lead the Credit Risk Engineering team, setting technical direction, planning delivery, mentoring engineers, reviewing code, and contributing hands‑on to critical work.
• Design, build, and operate the backend services and APIs that integrate risk capabilities into Kiwi's lending products.
• Improve the reliability of credit decision flows across services and external dependencies, including API contracts, latency, timeouts, failure handling, observability, and incident response.
• Partner with Credit Risk and Data Science to integrate models into production and improve MLOps practices, including deployment automation, versioning, testing, monitoring, and rollback.
• Improve the architecture and maintainability of risk services and integrations, addressing technical debt while supporting the delivery of new risk capabilities.

Skills

TypeScript

Node.js

Python

SQL

PostgreSQL

MLOps

AWS

Docker

CI/CD

Observability

API design

Microservices

Tools

FastAPI

LightGBM

scikit-learn

Snowflake

Airflow

dbt

GitHub Actions

Job description

Kiwi is seeking a hands-on Engineering Lead to guide the Credit Risk Engineering team, building backend services and APIs that power our lending platform. You will collaborate closely with Credit Risk and Data Science to deploy validated models into production and to improve MLOps, reliability, and deployment practices.

You will mentor engineers, drive technical direction, and ensure scalable, observable systems across Cloud (AWS) and containerized environments.