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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist, Applied AI - **Company:** CO-RIPPLING LLC - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Information Engineering, Data Systems, Database Queries, Software Debugging, Design of User Interfaces, Monitoring of Systems, Human-Computer Interaction, Python (Programming Language), Machine Learning, Software Product Management, Regression Testing, Reliability Engineering, Next.js, Software Engineering, SQL Databases, TypeScript, Web Application Frameworks, Usage Analysis, Retrieval-Augmented Generation, Large Language Models, Grafana, Multi-Agent Systems, Prompt Engineering, Backend, Langfuse — LLM Observability and Analytics Platform, Agentic-AI, Fastapi, LangSmith, Core Data, Front End Software Development, Invoking Functions, Automation Anywhere - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-scientist-applied-ai-san-francisco-ca--d5ae8a04-2a15-4228-a933-934a6db634f6 ## About the Role Artificial Intelligence (AI), Data Science, Sales, Market Analysis, Artificial Intelligence (AI) Agents, Artificial Intelligence (AI), User Interface/Experience (UI/UX), Reliability Engineering, Data Science, Product Development, * 3-6 years of experience across data science, applied ML, software engineering, data engineering, or applied AI, including 2+ years of hands-on data science or applied ML work and 1-2 years building or operating production LLM-powered applications. * Experience in a data science or applied ML role, including building models, designing analyses or experiments, working with business/product data, and translating findings into product or operational impact. * Strong Python skills, with experience owning backend services, APIs, or production AI/data systems. Experience with FastAPI or an equivalent backend framework is a plus. * Hands-on experience building production LLM systems, including prompt design, retrieval-augmented generation, tool/function calling, context management, agent orchestration, evaluation, and runtime quality controls. * Strong SQL skills for data analysis, debugging, and building reliable data/context pipelines. * Experience analyzing usage, quality, or performance data and using those insights to improve product or system behavior. * Comfortable owning end-to-end workstreams in ambiguous, fast-moving environments, from problem framing through production launch and iteration., * Experience with AI evaluation or observability tools such as LangSmith, Braintrust, Langfuse, Arize, or similar. * Background in experimentation, product analytics, or GTM analytics. * Experience with Next.js, TypeScript, or other modern frontend frameworks. * Experience building internal tools or AI products for Sales, Customer Success, RevOps, Support, or other B2B SaaS teams. * Strong product judgment and ability to communicate technical tradeoffs to non-technical partners. ## Description Rippling's Go-to-Market Analytics team owns a growing suite of internal AI agents and applications used daily by Sales, RevOps, and Customer Success. We're looking for a senior applied AI builder to help evolve this stack: improving the reliability, quality, and user experience of existing agents while designing and shipping new AI workflows that automate high-leverage GTM processes, surface better business insights, and help teams move faster. This is a hands-on, high-ownership role on a small team that blends applied AI product development with core data science, ML, and analytics work. You will work across the full applied AI stack: backend systems, data and context pipelines, agent workflows, internal product experiences, and the evaluation and observability systems that make AI quality measurable. What you will do * Build, launch, and improve AI agents, workflows, and internal applications used by Rippling's GTM teams. * Design new agent workflows involving retrieval, tool use, structured context, multi-step reasoning, and human-in-the-loop review. * Own full-stack feature development for internal AI products, from Python/FastAPI backend services and APIs to Next.js/TypeScript frontend experiences. * Create SQL/Python pipelines that assemble trusted business context from GTM, product, account, and activity data. * Apply core data science and ML techniques, including experimentation, predictive modeling, segmentation, forecasting, and product analytics, to identify opportunities, improve GTM workflows, and power AI product features. * Build and improve the model and agent evaluation infrastructure used to measure quality, catch regressions, and guide iteration, including offline evals, golden datasets, regression tests, human review workflows, and LLM-as-judge evaluation patterns. * Analyze production traces, usage patterns, latency, token cost, and quality signals using tools such as LangSmith or similar observability platforms. * Debug and resolve issues across prompts, retrieval, context assembly, tool calls, integrations, latency, and system performance. * Partner with RevOps, Sales, Customer Success, and Data Science leaders to turn analytical insights and operational pain points into shipped AI product features. * Establish practical standards for AI quality, safety, monitoring, evaluation, and iteration across Rippling's internal AI product suite.