About 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 roleThe Growth Engineering team builds world-class products, data infrastructure, and AI systems powering Rippling's market intelligence and GTM operations. We work closely 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, Redis, and LLM APIs, enabling scalable experimentation and fast iteration.
What you will do- Build polished frontend experiences in React and TypeScript for AI-native GTM workflows, including chat interfaces, generated artifact viewers, skill libraries, embedded tools, and data-rich account/customer views.
- Develop full-stack product features across Next.js, FastAPI, Python, PostgreSQL, Redis, and data/LLM-backed services.
- Design and improve multi-turn AI chat experiences that maintain conversation state, tool-call context, attachments, user memory, and follow-up intent across long-running GTM workflows.
- Build agentic workflows using LangChain, LangGraph, and related orchestration patterns, combining LLM reasoning with deterministic tools, structured data, retrieval, and human-in-the-loop UX.
- Instrument AI workflows with LangSmith tracing, evaluation datasets, regression tests, and quality metrics so the team can measure answer quality, tool usage, latency, cost, and failure modes over time.
- Create and maintain evals for AI-generated briefings, reports, analytics answers, HTML artifacts, and multi-turn conversations, helping the team ship model and prompt changes with confidence.
- Partner with PMs, designers, sales, RevOps, Applied AI, and data engineering to turn ambiguous GTM problems into simple, high-leverage product experiences.
- Own features end to end, from product behavior and API design to frontend polish, observability, testing, and production rollout.
What you will need- 3+ years of professional software engineering experience, with strong frontend experience in React and TypeScript.
- Experience building full-stack product features with modern backend frameworks, ideally Python and FastAPI or similar.
- Hands-on experience building LLM-powered products, especially multi-turn chat, agent workflows, tool calling, retrieval, structured outputs, or generated artifacts.
- Experience with LangChain, LangGraph, LangSmith, or similar AI orchestration, tracing, and evaluation frameworks.
- Ability to design and run AI evals, debug model behavior, inspect traces, improve prompts/tools, and reason about quality across multi-turn conversations.
- Strong product intuition and a high bar for UX, interaction design, frontend quality, and performance.
- Ability to reason across frontend state, backend APIs, data models, async jobs, permissions, observability, and production debugging.
- Experience working with data-rich products, internal tools, analytics workflows, CRM systems, or GTM/sales/customer-facing systems is a strong plus.
- Clear communication skills and the ability to collaborate with technical and non-technical stakeholders.
- A bias toward ownership, practical execution, and building systems that make users meaningfully faster and better at their jobs.
Additional InformationRippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email
Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a defined radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.
This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.
A variety of factors are considered when determining someone's compensation-including a candidate's professional background, experience, and location. Final offer amounts may vary from the amounts listed below.
The pay range for this role is:
135,000 - 225,000 USD per year (US Tier 1)
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