Head of Artificial Intelligence

At AI Case Leads, we connect accident victims with personal injury law firms across the United States. AI is already part of how we work: our developers, managers, and reps all use it every day. But we’re using a fraction of what it can do. We need a Head of AI to make AI a real advantage across the whole company: how we build, how we work, and how we understand our own business.

The Role

You’ll own AI strategy and execution company-wide. That covers four areas:

1. Build the company brain. A central knowledge system where every call transcript, conversation, and key data source comes together, so anyone can get full context on any part of the business.
2. Level up engineering. Make sure our developers use the best models and tools in the smartest way, and that AI-generated code meets a high bar before it ships.
3. Educate the team. Teach everyone, from leadership to reps, how to use AI well, including how to prompt properly.
4. Stay ahead. Track new models and tools, test them fast, and bring the ones that matter into our workflows.

You’ll be hands-on. This is a builder and teacher role, not a slide-deck role.

What You’ll Do

Company brain

• Design and build a central AI knowledge system that ingests call transcriptions, Slack, CRM data, documents, and other company sources
• Make it searchable and usable so managers and team members can ask questions and get accurate answers with sources
• Set up pipelines that keep the brain current automatically
• Build in access controls and redaction so sensitive customer information is protected and only visible to the right people

Engineering and AI tooling

• Define how our dev team uses AI: which models, which tools, and when to use each
• Set up model routing so complex work goes to top-tier models and routine work goes to faster, cheaper ones, keeping us productive without hitting limits or overspending
• Audit AI-generated code and output from the dev team to catch low-quality work, security issues, and bugs before they reach production
• Create standards for AI-assisted development: review checklists, testing expectations, and what “done” looks like
• Monitor AI usage and spend across the company and optimize it

Education and enablement

• Train managers, team leads, and employees on effective prompting and practical AI use for their specific roles
• Run workshops, office hours, and one-on-one coaching sessions
• Build a shared library of prompts, templates, and workflows for each team
• Measure adoption and help teams find the highest-impact places to apply AI

Research and adoption

• Track new model releases, tools, and techniques, and judge what’s real versus hype
• Test promising tools quickly and roll out the winners
• Identify processes across the company that AI can automate or improve
  

What We’re Looking For

• 4+ years in software engineering, with deep hands-on experience building with LLMs
• Experience building RAG systems, knowledge bases, or AI search over large volumes of unstructured data (transcripts, documents, chats)
• Strong working knowledge of current frontier and open models (Claude, GPT, Gemini, and others), with an understanding of their strengths, costs, and limits
• Experience with model routing, fallback strategies, and managing AI costs and rate limits
• Strong code review skills, including the ability to spot weak AI-generated code fast
• Proficiency in TypeScript and/or Python
• Experience with AI coding tools and agentic workflows
• A real talent for teaching: you can explain AI to a developer and to a call center rep
• Experience handling sensitive data securely in AI systems
• Experience with speech-to-text or call transcription pipelines (a plus)
• Experience in a call center, sales, or lead-gen environment (a plus)
• Experience integrating AI with CRMs, dialers, or automation platforms (a plus)
  

How You Work

• You build first. You prototype in days, not quarters.
• You have high standards. You’ll tell a developer their AI-generated code isn’t good enough, and show them how to fix it.
• You teach patiently. You meet people where they are and make them better.
• You’re practical about hype. New isn’t automatically better; you test and decide.
• You’re self-directed. You set the AI roadmap and drive it.
  

What Success Looks Like

• 90 days: the company brain is live with call transcripts searchable, model and tool standards are set for engineering, and every manager has had AI training.
• 6 months: teams use AI daily and effectively, code quality is up, AI costs are under control, and leaders can get answers about any part of the business in minutes.
• Long term: AI is a real competitive advantage for AI Case Leads, not just a tool people have open in another tab.
  

Why AI Case Leads

• Fully remote
• Build the AI function from scratch, with real authority
• Huge amounts of real data to work with
• A lean team with direct access to leadership; no layers of approval