Lead AI Engineer

Introduction to the Team & Role

AI is central to 360Learning’s strategy: our AI Squad ships agentic features that help users discover, create, and administrate content.

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

We’re now looking for a Lead AI Engineer to drive the technical vision for AI in 360Learning’s product and to coach our AI Engineers as the team grows. This is a hands-on leadership role: you’ll set technical direction, own the hardest architectural decisions, and grow the people around you, while staying close to the code.

You’ll coach our team of AI Engineers (2 today, growing), and partner closely with 1 Product Manager, 1 Product Designer, and our Full-Stack Developers. You’ll report directly to the Head of AI/Data.

What You’ll Do

Within 1 month, you will:

• Graduate in Convexity through our onboarding process and complete our coach training

• Understand our product offering, processes, and tools

• Get to know the AI Squad and your fellow AI Engineers

Within 3 months, you will:

• Build a global view of our codebase and architecture (Pydantic AI, FastAPI, Azure OpenAI, ElasticSearch)

• Contribute meaningfully to an existing feature, hands-on

• Become the point of contact for the squad’s technical topics

• Start coaching the AI Engineers: identifying their key strengths and areas for growth, and unblocking challenges proactively

• Become a trusted engineering partner to the squad’s PM and PD

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 cost, improve latency, and scale to handle usage spikes

• Lead Performance Reviews and Career Path assessments for your AI Engineers

• Set the technical direction for AI features alongside the PM’s product vision

• Share best practices and drive process improvements across the squad

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 expert the AI Engineers rely on, and define the next career steps for each of them with a concrete action plan

• Push technical innovation within the squad and across R&D (e.g. hackathons, transversal initiatives), keeping roughly 80% hands-on and ~20% on coaching and management

The Skill Set

The Skill Set

• 4+ years building GenAI / LLM-powered systems, with a track record of taking them from prototype to long-term production deployment

• Experience, formal or informal, as a tech lead, mentor, or coach for a team of engineers, ideally on a SaaS platform

• Strong Python experience, with a track record of clean, maintainable production code