Software Engineer (LLM Systems)

• 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 that maintain research-grade quality at scale

• If you love building novel data systems that turn raw signals into defensible, high-margin products, this is where you’ll do the most important work of your career

Benefits

• Medical, dental, and vision insurance

• 401K 3% match, immediate vesting

• Paid Vacation and Public Holidays

• Paid Sick Days

• Pre-tax commuter benefits

• Health Savings / Flexible Savings Account

• Paid Parental / Family Leave

• Office snacks and refreshments

• Lunch and learns

• Monthly team outings and bimonthly happy hours

• Annual company retreat

• Volunteering

• Virtual fun, social activities (e.g., happy hours, painting, escape rooms, trivia, cooking classes, meditation, and more!)- Customer focus: Ability to translate user needs into technical solutions while maintaining engineering best practices

• You write exceptional code, fast. 3-4 years of experience shipping production code in a fast-paced environment

• Full-stack expertise: Moderate proficiency in React, TypeScript, and modern frontend frameworks. Backend experience with Python, Node.js, or similar

• AI/ML implementation experience: Hands-on experience integrating LLMs, building with OpenAI/Anthropic APIs, or implementing ML models in production. We care more about a demonstrated eagerness to learn and an understanding of complex systems than specific years

• Quality mindset: Experience with testing, code reviews, and maintaining high code quality standards

• Cloud and infrastructure: Experience with AWS, Docker, and modern deployment practices

• RAG systems, embeddings, semantic search

• Real-time data processing or streaming architectures

• Open-source contributions in AI/ML