AI Engineer, Customer Success

Role overview Join a Customer Success organization as an embedded AI Engineer focused on building agentic solutions that help large enterprise customers unlock value from an IoT operations platform. This is a hands-on, full-lifecycle role where you will own everything from the first prompt through production iteration, partnering with Customer Success playbooks and product teams as new features and telemetry reshape requirements.

Responsibilities - Design, build, test, and deploy agentic AI applications that support hundreds of commercial customers managing fleets, equipment, and physical operations. - Maintain and continuously improve production agents as Customer Success workflows evolve and as new product capabilities ship. - Translate real-world usage data and field feedback into roadmap changes for the underlying AI infrastructure. - Collaborate with Customer Success managers and product engineers to identify high-leverage automation opportunities. - Uphold reliability, evaluation, and safety standards for customer-facing AI experiences.

Requirements - Hands-on experience as an applied AI engineer building production LLM- or agent-based systems end to end. - Strong proficiency with modern prompt engineering, evaluation harnesses, and orchestration frameworks. - Solid software engineering fundamentals, including testing, observability, and deployment practices. - Ability to work embedded with a non-engineering customer-facing team and translate ambiguous needs into shipped product. - Comfort owning systems in production and iterating on them as requirements shift.

Nice to have - Background supporting enterprise customers in IoT, logistics, transportation, construction, field services, or related physical-operations domains. - Familiarity with connecting AI workflows to data platforms, APIs, or device telemetry.