Staff AI Platform Engineer — Data Cloud & Applied ML

Rippling; San Francisco (CA); Presencial; USD 210.000 - 320.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Descripción de la vacante

Rippling's Data Cloud team is hiring a Staff Software Engineer to architect and build AI platforms for a unified data platform. You will own end-to-end schema retrieval, training pipelines, and RL environments, partnering with AI Platform, Infrastructure, Security, and Product Engineering to scale and de-risk AI features across the workforce system.

You will mentor engineers, drive technical direction, and contribute to multi-team initiatives while ensuring quality, reliability, and performance

Formación

• 8+ years of software engineering experience with distributed systems in production.
• Experience deploying and maintaining LLMs in production environments.
• Experience optimizing model inference at scale, including LLMs and embeddings.
• Backend proficiency in Python, Go, or Java.
• Cloud-native infra experience: Kubernetes, containers, observability, reliability.
• Ability to drive cross-functional technical strategy and execution.

Responsabilidades

• Build a state-of-the-art schema retrieval system over varied schemas.
• Scale AI training pipelines for data retrieval and model generation.
• Design RL training environments for structured/unstructured data retrieval.
• Develop agent harnesses for safe AI features on Data Cloud.
• Optimize model serving and inference for scale and UX.
• Collaborate with AI Platform, Infra, Security, and Product Eng to define standards.
• Provide technical leadership and mentor engineers across multiple teams.

Conocimientos

Distributed systems

LLMs in production

Backend engineering

Python

Go

Java

Cross-functional leadership

Herramientas

Kubernetes

Descripción del empleo

Rippling's Data Cloud team is hiring a Staff Software Engineer to architect and build AI platforms for a unified data platform. You will own end-to-end schema retrieval, training pipelines, and RL environments, partnering with AI Platform, Infrastructure, Security, and Product Engineering to scale and de-risk AI features across the workforce system.

You will mentor engineers, drive technical direction, and contribute to multi-team initiatives while ensuring quality, reliability, and performance