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