AI Engineer

About the Role

AI is central to 360Learning's strategy: our AI Squad ships agentic features that help users discover, create, and administrate content. As an AI Engineer, you'll architect and ship the next generation of these AI systems, from prototype to production.

You will join the AI Squad as its second AI Engineer, working closely with 1 peer AI Engineer, 1 Product Manager, 1 Product Designer, and 4 Full-Stack Developers. You will own the technical strategy for AI features while collaborating directly with product, design, and engineering.

What We've Built

Over the last year, we have shipped 5+ AI features powering thousands of users monthly:

• Catalog Companion: An AI agent performing bulk catalog operations (sharing, archiving, tagging, author assignments)
• Smart Search: conversational search helping users discover the right content
• Conversational BI: Analytics and insights delivered through natural conversation
• AI Course & Question Generation: Creating questions and full courses from documents and titles
• Content Recommendations: Personalized content discovery

Within 1 month, you will:

• Graduate in Convexity through our onboarding process
• Understand our product offering through training
• Meet the team through virtual coffee meets and happy hour
• Learn our processes and tools

Within 3 months, you will:

• Get a global view of our codebase and architecture (Pydantic AI, FastAPI, Azure OpenAI, ElasticSearch)
• Contribute meaningfully to an existing feature

Within 6 months, you will:

• Own end-to-end delivery of a new AI feature: from technical design through production launch
• Optimize for real-world constraints: reduce per-request costs, improve latency, scale to handle usage spikes

Within 12 months, you will:

• Make architectural decisions as we scale from 5 to 10+ features
• Prototype and ship advanced capabilities: new modalities, real-time collaboration
• Be the technical authority for your peers

The Skill Set

• 2 years of experience taking GenAI / LLM-powered systems from prototype to long-term production deployment
• Strong Python experience, with a track record of clean, maintainable production code
• Hands-on experience integrating LLM (Azure OpenAI, OpenAI, Anthropic, Mistral, etc.) and managing real-world constraints: token costs, latency, reliability, hallucinations
• Familiarity with search capabilities, RAG, semantic search, vector databases, agents, LLM observability tools (Langfuse or similar), and evaluation of models
• Solid grasp of Machine Learning fundamentals (evaluation, experimentation, model lifecycle)
• Fluent English (US/UK) / B2 level or equivalent (FR)

Interview Process

1. Phone Screen with our Talent Acquisition Manager
2. Discovery Meeting with a ML Engineer
3. System Design with a Software Architect and our Tech Lead
4. Clarification Meeting with our Senior Data Manager
5. Culture Fit Meeting with our VP of Engineering
6. Offer!