Senior Applied AI Engineer for GTM Analytics

Rippling; San Francisco (CA); On-site; USD 138,000 - 230,000; Full time

Job summary

Rippling’s GTM Analytics team seeks a senior applied AI builder to enhance internal AI agents and workflows. You will own end-to-end AI product work across backend, data pipelines, and frontend experiences, shipping high-leverage AI features for Sales, RevOps, and Customer Success.

You will design robust agent workflows, manage retrieval and tool calls, and apply ML to surface insights and accelerate GTM processes.

Qualifications

• 3–6 years in data science, ML, software data engineering, or applied AI.
• 2+ years hands-on data science or ML work, 1–2 years building/operating production LLM apps.
• Strong Python skills with backend or production AI systems; FastAPI a plus.
• SQL skills for data analysis, debugging, and pipelines.

Responsibilities

• Build, launch, and improve AI agents, workflows, and internal apps for GTM teams.
• Design retrieval-augmented workflows with tool calls and human-in-the-loop review.
• Own full-stack development from Python backends to Next.js/TypeScript frontends.
• Create pipelines to assemble business context from GTM, product, and activity data.
• Apply ML techniques to improve GTM workflows and power AI features.
• Develop model/evaluation infra to measure quality and catch regressions.
• Analyze traces, usage, latency, and costs to improve system performance.
• Collaborate with RevOps, Sales, CS, and Data Science leaders to ship features.
• Establish standards for AI quality, safety, monitoring, and iteration.

Skills

Python

SQL

LLM systems

FastAPI

Data analysis

Backend services

Tools

LangSmith

Langfuse

Braintrust

Job description

Rippling’s GTM Analytics team seeks a senior applied AI builder to enhance internal AI agents and workflows. You will own end-to-end AI product work across backend, data pipelines, and frontend experiences, shipping high-leverage AI features for Sales, RevOps, and Customer Success.

You will design robust agent workflows, manage retrieval and tool calls, and apply ML to surface insights and accelerate GTM processes.