Engineering Lead: Credit Risk & ML Systems (Remote)

kiwi; Colombia; Remote; COP 120,000,000 - 180,000,000; Full time

Job summary

Kiwi is seeking a hands-on Engineering Lead to guide the Credit Risk Engineering team responsible for embedding risk capabilities into our lending products. You will mentor engineers, shape technical direction, and contribute code and reviews across services.

You will partner with Credit Risk and Data Science to productionize models, improve MLOps, and ensure reliable, scalable risk platforms that support fast, defensible lending decisions.

Qualifications

• Hands-on system design, implementation and production support experience.
• Proven backend experience with microservices and APIs.
• MLOps in production including deployment, monitoring and rollback.
• Collaboration with Credit Risk and Data Science teams.
• Strong SQL/PostgreSQL, data quality troubleshooting.

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

MLOps

Python

AWS

SQL

PostgreSQL

CI/CD

Docker

Tools

FastAPI

Snowflake

dbt

Airflow

LightGBM

scikit-learn

Job description

Kiwi is seeking a hands-on Engineering Lead to guide the Credit Risk Engineering team responsible for embedding risk capabilities into our lending products. You will mentor engineers, shape technical direction, and contribute code and reviews across services.

You will partner with Credit Risk and Data Science to productionize models, improve MLOps, and ensure reliable, scalable risk platforms that support fast, defensible lending decisions.