Rippling provides a unified platform to manage and automate every part of the employee lifecycle including HR, IT, and Finance systems
Job Summary
Rippling provides a unified platform to manage and automate every part of the employee lifecycle including HR, IT, and Finance systems.
The Growth Engineering team builds AI systems and data infrastructure powering market intelligence and GTM operations using modern technologies like Kubernetes, Databricks, and OpenAI APIs.
This role offers hands-on engineering leadership to own AI/ML technical strategy, mentor engineers, and solve complex production AI challenges with immediate business impact.
Matching Summary
Rippling provides a unified platform to manage and automate every part of the employee lifecycle including HR, IT, and Finance systems.
Skills & Requirements
Must-have
production ML systems development
recommendation engines and personalization models
LLM integration with OpenAI and Claude
Databricks and Spark pipelines
MLOps workflows and tooling
Kafka and data engineering
FastAPI and Kubernetes deployment
Nice-to-have
LangChain and LangSmith familiarity
multi-LLM coordination and prompt routing
AI safety and interpretability frameworks
containerized AI services deployment
feature stores and experiment tracking
Key Requirements
7+ years software engineering experience
3+ years building production ML systems
Experience with recommendation and personalization models
Proven ability to architect scalable AI systems
Experience deploying models in Databricks and Spark
Strong data engineering skills with Kafka and PostgreSQL