Staff Software Engineer - AI

Staff Software Engineer - AIAbout RipplingRippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.Based in San Francisco, CA, Rippling has raised $1.4B+ from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.About the TeamThe Growth Engineering team builds world-class products, data infrastructure, and AI systems powering Rippling’s market intelligence and GTM operations. The team works cross-functionally with sales, marketing, Applied AI, and data engineering teams to design systems that amplify Rippling’s high-performance GTM engine — from recommendation models and enrichment pipelines to AI-driven workflows and proprietary data funnels.We operate on a modern Growth Services infrastructure built on FastAPI, Kubernetes, Databricks, Kafka, Snowflake, PostgreSQL, and OpenAI APIs, enabling scalable experimentation and fast iteration.About the RoleWe’re seeking a Staff AI/ML Engineer to architect and lead development of production-grade AI systems, including recommendation engines, multi-LLM architectures, and ML pipelines. You’ll be responsible for designing systems that combine real-time data processing, ML/LLM Ops, and intelligent orchestration across Rippling’s Growth Infrastructure.This is a hands-on engineering leadership role — you’ll own the technical strategy for AI/ML within Growth Engineering, mentor engineers, and solve some of the most complex challenges in production AI systems with immediate business impact. What you will doAI/ML Architecture & Systems DesignArchitect, build, and optimize recommendation engines, personalization systems, and classification models for GTM automationDesign and implement multi-LLM architectures combining OpenAI, Claude, and Databricks models for intelligent decisioning and reasoningBuild, train, and evaluate modelsDeploy and serve models using FastAPI, Kubernetes, and async microservices, with observability built inDevelop MLOps workflows for fine-tuning, retraining, model versioning, and automated evaluationData Engineering & Model PipelinesDesign medallion data architectures (Bronze/Silver/Gold) using Databricks Delta Live Tables and CDC patternsBuild real-time and batch data pipelines leveraging Kafka and Databricks for high-volume model inputsDevelop and maintain embedding systems and matrix factorization-based recommendation frameworks for personalization and rankingImplement AI data quality and monitoring frameworks to ensure reliability and trust in model outputsAI Reliability, Observability & OptimizationImplement AI observability (LangSmith, Braintrust) to track performance, bias, and driftBuild fallback and routing systems for multi-model deploymentsOptimize cost and latency through batching, caching, and adaptive model selectionTechnical Leadership & CollaborationLead design reviews and guide architecture for AI/ML-driven systemsMentor engineers on LLM integration, MLOps, and recommendation systemsCollaborate closely with product and GTM partners to translate business goals into AI-driven automationWhat you will need7+ years of software engineering experience, including 3+ years building production ML systems.Expertise in recommendation engines, matrix factorization, and personalization models.Deep experience integrating LLMs (OpenAI, Claude, etc.) into...