Rippling 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.

The Revenue Operations team is dedicated to aligning a company’s go-to-market (GTM) functions across Marketing, Sales, Customer Success, and related operations to power growth and optimize the revenue engine. The core remit of RevOps is to drive predictable and efficient growth by optimizing processes, data, systems, and insights that power the end-to-end customer lifecycle.

The team partners very closely with the Sales, AI/ML, and Data Engineering teams to build solutions that amplify the effectiveness and efficiency of the Rippling Sales org – from recommendation models and AI-driven enrichment pipelines to proprietary data funnels.

The broader team works on a modern Growth Services infrastructure built on FastAPI, Kubernetes, Databricks, Kafka, Snowflake, PostgreSQL, and OpenAI APIs, enabling rapid experimentation and scalable delivery of AI-powered systems.

We are looking to bring on a talented GTM minded Data Engineer to join the team. The ideal candidate wants to work in an agile environment close to the business and is not tied down to one specific product, but rather is a catalyst of innovation serving various business needs and pains. You will design and implement backend services, AI integrations, and data pipelines that power Rippling’s sales automation stack – including account/lead enrichment, recommendation engines, AI-powered workflows in CRM, and multi-LLM orchestration frameworks.

You’ll work closely with AI/ML engineers, data scientists, and sales partners to bring production-grade AI systems to life, while maintaining reliability, performance, and developer velocity.

• Design and implement scalable backend systems that power AI/ML-driven recommendation, ranking, and personalization workflows.
• Build and maintain multi-LLM applications using OpenAI, Claude, and custom Databricks models, integrating them into real-time workflows.
• Develop and optimize data pipelines for model training, enrichment, and scoring using Databricks, Snowflake, and Kafka.
• Collaborate on AI/ML pipeline development, training and deploying models such as XGBoost, classification systems, and matrix factorization-based recommenders.
• Design and maintain scalable data pipelines that unify data across CRM, product systems, marketing platforms, billing systems, and internal databases
• Build internal tools and APIs to support feature generation and GTM evaluation frameworks for AI models.
• Partner with Growth Engineering and GTM stakeholders to translate growth initiatives into scalable AI and data systems.

• Backend & APIs: Python, FastAPI, SQLAlchemy, Pydantic, PostgreSQL, Redis
• Frontend (if applicable): Next.js 14, React, TypeScript, Tailwind CSS, Radix UI
• Data & ML Infrastructure: Databricks, Delta Live Tables, Snowflake, Polars, PyArrow, Kafka, Debezium
• AI/ML Systems: OpenAI, Claude, LangChain, XGBoost, matrix factorization, recommendation systems
• Observability: Braintrust, LangSmith, DataDog, custom evaluation metrics
• Infrastructure: Docker, Kubernetes, AWS, automated CI/CD pipelines

• 3+ years of professional software engineering experience (preferably in backend, data, or AI-focused roles).
• Strong Python development and system design skills.
• Experience building production-grade services or data-intensive applications.
• Familiarity with AI/ML systems, including model training, inference APIs, or recommendation engines.
• Experience working with data platforms such as Databricks, Snowflake, or Kafka.
• Experience working with GTM teams (sales/marketing/RevOps/Sales Ops)
• Excellent communication skills and ability to collaborate cross-functionally in a fast-paced environment.

• Competitive salary, significant equity, and comprehensive benefits
• Opportunity to work on cutting-edge AI/ML and data infrastructure
• Direct hands-on exposure to high-growth GTM businesses
• High ownership and autonomy in a fast-growing team
• Collaborative environment focused on technical excellence and real business impact