AI Evangelist - Program Manager

About the role

Axon's Corporate AI Team sits within the Enterprise Data organization and focuses on internal-facing AI solutions that help Axon employees do more high-value work with less manual effort. The team builds and operates Cortex, Axon's internal AI platform that provides GPT-class models, chat assistants, and secure integrations with systems like Quip, Jira, Slack, Microsoft 365, Snowflake, and more.

We're looking for an AI/Technology Evangelist to drive the adoption, understanding, and responsible use of AI across Axon. In this role, you'll:

• Be the bridge between the Corporate AI Team's capabilities and the rest of the organization—translating what's possible into what's practical.
• Design and deliver training programs, workshops, demos, and enablement materials that help employees at every level use AI tools effectively and safely.
• Identify high-impact AI use cases across business units, champion them from concept to adoption, and measure their impact.
• Build and maintain the internal AI playbook—guides, best practices, templates, and reference materials that make it easy for teams to build with AI.

Responsibilities

• Adoption & Enablement
• Design, build, and deliver training programs (workshops, office hours, lunch-and-learns, self-paced content) that help Axon employees effectively use AI tools including Cortex, Claude, Copilot, and internal AI-powered applications.
• Create and maintain a library of enablement materials—quick-start guides, prompt engineering playbooks, video walkthroughs, FAQs, and best-practice documentation.
• Run an internal AI champions program (e.g., Champions Circle) to cultivate power users across business units who can drive adoption within their teams.
• Track and report on adoption metrics—usage, engagement, satisfaction, and business impact—to measure progress and identify gaps.

• Use Case Discovery & Delivery
• Partner with teams across Axon (Finance, Sales, Operations, Legal, HR, Support, Engineering) to identify workflows where AI can meaningfully reduce toil, improve quality, or create leverage.
• Prioritize use cases based on impact, feasibility, and alignment with Axon's mission; work with the Corporate AI Team to scope and deliver solutions.
• Build lightweight prototypes and demos that show teams what's possible before committing engineering resources.
• Document and share success stories—quantified wins, before/after workflows, and lessons learned—to build momentum across the organization.

• Communication & Storytelling
• Serve as the primary internal voice for Axon's AI platform—communicating roadmap updates, new capabilities, best practices, and success stories to all levels of the organization.
• Create compelling content (blog posts, internal newsletters, Slack updates, demo videos, presentations) that keeps AI visible and accessible.
• Present to leadership and executive audiences on AI adoption progress, emerging opportunities, and strategic recommendations.
• Represent Axon's Corporate AI work externally where appropriate—conferences, meetups, industry events, and thought leadership content.

Requirements

• Bachelor's degree in Computer Science, Engineering, Communications, or a related field, or equivalent practical experience.
• 8+ years of experience in technology roles, with at least 3 years focused on AI/ML, developer relations, technical evangelism, enablement, or a closely related domain.
• Demonstrated ability to explain complex technical concepts to non-technical audiences—in writing, in presentations, and in one-on-one conversation. This is the core skill.
• Hands-on experience with modern AI tools and platforms (LLMs, coding assistants, automation frameworks, cloud AI services). You don't need to be a researcher, but you need to be a skilled practitioner.
• Strong understanding of software development practices, cloud infrastructure, and enterprise technology stacks—enough to have credible technical conversations with engineers.
• Track record of driving technology adoption or transformation initiatives within an organization. You've changed how people work, not just told them to.
• Self-directed and comfortable operating with ambiguity. You don't wait for a roadmap—you build one.
• Strong communication and collaboration skills, with comfort working across every level of an organization, from individual contributors to C-suite executives.

Qualifications

• Content creation skills—writing, video production, or visual design experience that helps you create compelling enablement materials.
• Public speaking experience—conferences, webinars, all-hands presentations, customer events.
• Experience in developer relations, developer advocacy, technical evangelism, or technical training at a technology company.
• Hands-on work with LLM platforms and tools, such as OpenAI (ChatGPT / APIs), Anthropic (Claude / Claude Code), AWS Bedrock, Azure OpenAI, or similar.
• Experience building and running internal enablement programs—training curricula, champions programs, office hours, documentation libraries.
• Familiarity with AI governance, responsible AI frameworks, and compliance requirements (CJIS, FedRAMP, SOC 2).
• Experience integrating with enterprise systems like Jira, Confluence/Quip, Slack, M365, Salesforce, or Snowflake—enough to understand what's possible and demo it.
• Understanding of prompt engineering, RAG architectures, agentic workflows, and AI evaluation methods.

Skills

• Hands-on experience with modern AI tools and platforms (LLMs, coding assistants, automation frameworks, cloud AI services).
• Strong understanding of software development practices, cloud infrastructure, and enterprise technology stacks.
• Ability to explain complex technical concepts to non-technical audiences.
• Experience in developer relations, developer advocacy, technical evangelism, or technical training.
• Experience building and running internal enablement programs.
• Familiarity with AI governance, responsible AI frameworks, and compliance requirements.
• Experience integrating with enterprise systems.
• Understanding of prompt engineering, RAG architectures, agentic workflows, and AI evaluation methods.