LLM Full Stack Software Engineer

What's Novo AI?

We're transforming the trillion-dollar insurance industry with generative AI that delivers real results. Our proof? We've already helped April International reduce manual health invoice processing by 80% while improving accuracy. Now we're expanding this technology across the insurance landscape. Want to be part of this transformation?

Why join us?

• Build real AI solutions that directly impact the insurance industry (not just chatbots!)
• Work with cutting-edge LLM models and techniques in production environments
• Collaborate with experienced ex-Google engineers in a high-impact role
• Drive meaningful projects that shape our product development

What you'll work on

• Architect and implement robust, scalable Typescript-based full-stack solutions for insurance document processing
• Design and optimize RAG pipelines, embedding strategies, and modern LLM implementations
• Tackle complex challenges like extracting structured data from unstructured medical documents

Requirements

• 2+ years of professional software engineering experience
• Strong proficiency in JavaScript/TypeScript and modern web frameworks
• Demonstrated experience building production-grade applications
• Experience with AI/LLM implementations preferred
• Excellent problem-solving and system design skills
• Strong communication abilities and experience working in remote teams

Nice to have

• Experience with RAG, embeddings, and other LLM techniques

What makes us different

• Work directly with experienced technical leaders
• Significant autonomy and ownership of technical decisions
• Remote-first culture focused on impact
• Opportunity to shape core product architecture

Time Commitment

Flexible between part-time and full-time - we value impact over strict schedules. This role is ideal for experienced engineers looking to transition into AI engineering or seeking flexible work arrangements.

Location

Fully remote position with flexible hours.

Interested?

We're particularly interested in hearing about your production engineering experience, any AI/ML projects you've worked on, and your approach to technical problem-solving.