Risk Data & AI Engineering Lead — Remote

Ladders; United States; A distancia; USD 120.000 - 194.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Tech setup provided

Remote connectivity allowance

Flexible WFH policy

Virtual interview support

Descripción de la vacante

Ladders seeks a Managing Engineer - Risk Data & AI (Remote, US) to lead a team building data and AI solutions for risk management in the Finance & Insurance sector.

You will shape engineering direction, drive data quality and reliability, and translate business requirements into scalable, production-ready capabilities while collaborating with product and engineering teams.

This is a hands-on leadership role with architecture, delivery coaching, and modern practices like MLOps.

Formación

• 5+ years in data, analytics, or AI engineering with Python and/or Java.
• 2+ years leading engineering teams focused on architecture and delivery.
• Experience delivering AI-enabled applications and automations; strong CI/CD and DevSecOps familiarity.

Responsabilidades

• Lead a team focused on data products and AI applications.
• Set technical direction for data and AI engineering initiatives.
• Contribute hands-on to architecture and design decisions.
• Own production outcomes for reliability and data quality.
• Collaborate with product managers and engineering teams to align priorities.
• Drive modern engineering practices like TDD and MLOps.
• Translate business requirements into scalable data and AI solutions.

Conocimientos

Python

Java

Data engineering

AI engineering

Team leadership

Herramientas

APIs

Backend services

Data pipelines

CI/CD

DevSecOps

Descripción del empleo

Ladders seeks a Managing Engineer - Risk Data & AI (Remote, US) to lead a team building data and AI solutions for risk management in the Finance & Insurance sector.

You will shape engineering direction, drive data quality and reliability, and translate business requirements into scalable, production-ready capabilities while collaborating with product and engineering teams.

This is a hands-on leadership role with architecture, delivery coaching, and modern practices like MLOps.