Lead Applied AI Engineer - Legal EdTech

BARBRI has helped over 1.3 million law students pass the bar exam. Now we're embarking on our AI transformation journey. If you want to combine cutting-edge AI with a domain that matters, let's talk.

BARBRI is a legal education company with 58 years of legal credibility. For years BARBRI has been changing the lives of pre-law students, law students and lawyers on how they develop new skills.

Now, with the AI revolution, BARBRI is at a critical juncture. We must simultaneously adapt to new demands of learns from edTech products, break into a rapidly evolving Professional Education market and transform ourselves into an AI-native organization.

This is a senior IC role where you'll ship real systems: AI-powered simulations for legal training, workflow automations that move EBITDA, and AI features embedded into existing products. You'll work closely with the Head of AI, with hands-on coaching as you develop deeper AI/ML expertise. If this works, you'll help shape the team as it grows.

High autonomy. High visibility. Real impact on the product and the business.

First 90 days

• Build and deploy workflow automations (n8n, MS Copilot agents) that solve real problems in Sales, RevOps, and Support

• Stand up data pipelines and integrations across our stack (Salesforce, Freshdesk, MS365 Cpilot)

• Get hands-on with LLM APIs - prompt engineering, RAG basics, evaluation frameworks

• Rapidly prototype and test working solutions (LLM agents, workflow automations, microapps, embedded tools, etc.)

Beyond 90 days

• Own our simulation product — voice AI, LLM orchestration, context management

• Launch AI features into existing BARBRI products — identify high-value integration points and ship them

• Enable non-technical teams to build their own AI agents and automations — act as the expert they can lean on

• Architect system integrations across our tooling ecosystem

• As the team grows, provide technical direction — own architecture decisions, mentor new engineers, manage vendors

• Build RAG pipelines, multi-agent orchestration, and real-world task integration.

• Support and improve existing Knowledge Retrieval (search, recommendations, course assistant) projects

Projects

• AI Simulation Engine: Conversational AI that helps lawyers practice soft skill — (currently in customer discovery)

• Workflow Agents: AI-powered automations for Sales, RevOps, and Support that move EBITDA

• Product AI: Embedding AI capabilities into existing BARBRI learning products

Who You Are

Must Have

• Strong Python skills — data processing, API integrations, backend services

• 5+ years building production backend or data engineering systems

• Hands-on LLM experience: RAG architectures, prompt engineering, evaluation frameworks

• Full-stack capability: You can build the API, connect the frontend, and deploy it yourself

• Bias toward shipping: You optimize for "working in production" over "theoretically optimal"

• Comfort with ambiguity: you can take direction early and grow into ownership

Strong Plus

• Azure fluency: You know your way around Azure infrastructure—App Services, Functions, Cognitive Services, or OpenAI deployments

• Search/retrieval experience: You've built semantic search, hybrid search, or information retrieval systems

• MS365 ecosystem experience (Copilot Studio, Graph API, Azure OpenAI)

• Workflow automation platforms (n8n, Zapier, or similar)

• Voice/speech AI experience (STT/TTS integration, latency optimization)

• Legal domain knowledge or experience building for regulated industries

• Experience at early-stage startups or building 0-to-1 products

• Node.js/TypeScript for backend services

Mindset

• Self-directed: You don't wait for tickets. You identify what matters and go build it.

• Pragmatic: You'd rather ship a good solution today than a perfect one never

• Curious about domain: Legal ed is niche - you're excited to learn how legal education works

• Low e