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Software Engineer

NewtonX | Built In NYC

New York, NYRemote OKFull-time$140k – $220k / year

About this role

Software Engineer - LLM Systems - NewtonX | Built In NYC NewtonX Software Engineer - LLM Systems Reposted 4 Days Ago Remote Hiring Remotely in USA 180K-220K Annually Mid level Remote Hiring Remotely in USA 180K-220K Annually Mid level Build and own core LLM infrastructure for two products: self-serve research workflows and automated syndicated intelligence. Implement full-stack features (React/TypeScript front end, Python/Node.js back end), integrate LLMs (OpenAI/Anthropic), design semantic search and RAG pipelines, ensure cloud deployment (AWS, Docker), maintain testing and code quality, and translate user needs into scalable, research-grade AI systems. The summary above was generated by AI About NewtonX NewtonX is a B2B insights company trusted by the world's most innovative companies to make high-stakes decisions with confidence. We combine a verified network of business professionals with AI-powered research tools to deliver research intelligence faster, more precise, and more defensible than traditional methods.Our clients include Google, Microsoft, TikTok, DoorDash, Stripe, and Coinbase. Our research has been cited by Fortune, Forbes, TechCrunch, Adweek, and the Wall Street Journal.NewtonX has raised $47M from investors including Two Sigma Ventures, Third Prime, XFund, and Citi Ventures. About The Role In this role, you'll own the core LLM infrastructure powering two products redefining B2B research: Hub – The central cockpit for B2B research. Build self-serve features that compress weeks into days: question → expert insight → follow-up, powered by RAG and adaptive workflows. Prime – Syndicated intelligence at scale. Architect automated systems that continuously capture expert opinions—creating longitudinal datasets and refreshable dashboards that compound in value. The technical challenge: fusing structured survey data with unstructured expert knowledge, building semantic search across proprietary corpora, and creating AI pipelines th

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