AI Infrastructure Engineer

Join Axon and be a Force for Good.

At Axon, we’re on a mission to Protect Life. We’re explorers, pursuing society’s most critical safety and justice issues with our ecosystem of devices and cloud software. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other.

Life at Axon is fast-paced, challenging and meaningful. Here, you’ll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter.

AI Infrastructure Engineer, Corporate AI Team

Team & Role Overview

Axon’s Corporate AI Team sits within Business Technology and builds internal-facing AI solutions that help employees reduce manual work, move faster, and focus on higher-value work. The team develops AI-powered tools, internal applications, integrations, and automation workflows used across Axon.

We’re looking for an AI Infrastructure Engineer to help move internal AI and software prototypes from “it works” to “it is production-ready, secure, reliable, supportable, and maintainable.” This role focuses on the operational backbone of internal applications: infrastructure, CI/CD, deployment patterns, reliability, maintenance, support, and production readiness.

This is a hands-on individual contributor role that blends platform engineering, DevOps, internal tools engineering, and applied AI infrastructure. You’ll work closely with Corporate AI, IT, Enterprise Data, Security, and business teams to support applications that replace existing software, augment workflows, and improve how teams operate.

We’re open to candidates at multiple levels. This could be a strong platform or DevOps engineer ready to grow into broader ownership, or an experienced infrastructure engineer who has operated internal systems at scale.

• Own maintenance, support, and operational readiness for internal AI-enabled applications and tools.

• Help productionize prototypes built by Corporate AI, business teams, or technical partners.

• Improve infrastructure and deployment patterns, with a focus on Vercel-hosted applications and tools deployed across Azure, AWS, and other environments.

• Build and maintain CI/CD, infrastructure-as-code patterns, monitoring, secrets management, access controls, runbooks, and support processes.

• Partner through testing, rollout, UAT, and long-term maintenance so internal tools remain useful, stable, secure, and dependable.

This is not an AI research role. You do not need to train models or develop novel ML techniques. You should understand how modern AI-powered applications are built, deployed, secured, monitored, and supported in an enterprise environment.

Productionize Internal Tools & Prototypes

• Turn prototypes, proof-of-concepts, and team-built tools into reliable applications for real business users.

• Improve production readiness across inherited applications, including deployment configuration, monitoring, error handling, documentation, testing, access controls, and supportability.

• Partner with Corporate AI engineers and business teams to move applications from prototype to pilot to production.

• Support UAT and rollout by helping validate that applications meet business needs, are stable for daily use, and have a clear support model.

• Identify reliability, security, scalability, and maintainability gaps before tools become business-critical.

• Ensure internal applications are not just built, but owned, supported, and continuously