Samsara
AI Engineer, Customer Success
$106K–$160K
Remote - Austin +6 · Remote · Full-time · Posted Jun 26, 2026
- Location
- Remote - Austin
Remote - CA
Remote - Chicago
Remote - Dallas
Remote - Houston
Remote - Seattle
Remote - CA - Experience
- 3+ years of software engineering or technical experience, with at least 1 year working hands-on with LLMs or AI agents in a production environment.
- Visa sponsorship
- Offers are contingent on the ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.
About the job
Build, deploy, monitor, and continuously improve customer-facing AI agents that support Samsara’s Commercial Customer Success team and improve customer outcomes.
What you'll do
- Design, test, deploy, and maintain agent architectures integrated with external systems and Customer Success tools.
- Create evaluation frameworks and automated tests; monitor production performance and iterate on agents as products and playbooks evolve.
- Partner with Customer Success to identify workflows and build solutions that support customer outcomes, risk mitigation, retention, and growth.
What they ask for
- Hands-on experience building and maintaining production LLM-based agents or automations.
- Python proficiency and experience connecting AI to external systems such as CRMs, APIs, customer data, and operational tools.
- 3+ years of software engineering or technical experience, including at least 1 year hands-on with LLMs or AI agents in production.
- Experience in a B2B SaaS environment.
Nice to have
- Experience with Anthropic Claude or similar LLM APIs; regression test suites or evaluation frameworks for non-deterministic AI systems.
- Background alongside Customer Success or Revenue Operations, or familiarity with Salesforce, Gainsight, or similar platforms.
Pay
$105,910 — $160,200 USD (base salary)
Tools
Python, Salesforce, Samsara platform, Anthropic Claude, Gainsight, LLMs
AI focus
Develop and own production customer-facing agentic AI solutions, including evaluation, deployment, monitoring, guardrails, and ongoing iteration to improve Customer Success outcomes.
Model-written summary · the original posting is authoritative