AI Engineer, Customer Success

Summary

Samsara is a company providing a Connected Operations Cloud that helps organizations using physical operations harness IoT data to improve safety, efficiency, and sustainability. The AI Engineer, Customer Success will build, deploy, monitor, and continuously improve customer-facing AI agents that support Customer Success workflows and improve customer outcomes, retention, and growth.

Responsibilities

• **Build:** Design agent architectures, write prompts, integrate with external systems (Salesforce, Samsara platform, Customer Success tools), and write clean Python code that the team can maintain
• **Test:**Define success criteria and evaluation frameworks before you write the first line of code. Build automated test suites that cover real-world scenarios, edge cases, and known failure modes
• **Deploy:** Own the deployment, versioning, and rollback plan for every agent. Ensure agents are production-ready before they reach CSMs or customers
• **Monitor:** Track agent performance in production — monitor accuracy, latency, failure rates, and customer outcomes. Detect drift before anyone has to tell you something's wrong
• **Maintain & Iterate:** Update agents continuously as Samsara's product evolves, Customer Success playbooks change, and real-world data indicates what needs improvement
• **Champion, role model, and embed Samsara’s cultural principles**(Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices
• Embed with the Commercial Customer Success team to understand what Customer Success Managers actually do — their workflows, their friction points, and the customer moments that move the needle
• Get fluent in Samsara's platform, data model, and existing Customer Success tooling stack
• Define success metrics and an evaluation framework for the first agent on the roadmap — before you write a single line of code
• Ship the first production agentic solution that meaningfully improves customer outcomes that lead to revenue retention and/or growth
• Build the monitoring and iteration loop from day one — so you have a clear signal on what's working, what's drifting, and what needs to change
• Spec the second agentic solution to detect and mitigate risk within accounts and start building, applying lessons from the first
• Provide an estimated start date for the value gap detection and product consultation — identifies underutilization and leads product consultations via text or call
• Own a portfolio of three or more production agentic solutions running reliably in the Commercial Customer Success motion — and a clear maintenance cadence that keeps them current as the product and playbooks evolve
• Demonstrate the impact of agentic solutions on reduced customer time to value, reduced time spent detecting and resolving risks, and increased retention
• Have a track record of improving solutions after launch: performance improvements measured in real customer outcomes, not just benchmark scores
• Be the go-to expert at Samsara for customer-facing agentic AI development — advising Customer Success leadership on what to build next, what to retire, and how to evaluate ideas before committing to them
• Help define what great looks like for ing at Samsara, setting a standard others can build on towards using AI to expand the pipeline

Skills

• This is a remote position open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area
• Hands-on experience building and maintaining production LLM-based agents or automations
• Python proficiency and a track record of connecting AI to external systems: CRMs, APIs, customer data, and operational tools
• The discipline to define what success looks like before you start building — and an eval framework that catches problems before your users do
• A genuine curiosity about Customer Success workflows and customer problems, not just the technical challenge
• Intellectual honesty about what AI can and can't do well — and the judgment to design guardrails and fallback paths accordingly
• 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
• Experience in a B2B SaaS environment
• Direct experience with Anthropic Claude or similar LLM APIs
• A background working with or alongside a Customer Success or Revenue Operations team
• Experience building regression test suites or eval frameworks for non-deterministic AI systems
• Familiarity with Salesforce, Gainsight, or similar CRM and Customer Success platforms

Qualifications

Must Haves

• This is a remote position open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area
• Hands-on experience building and maintaining production LLM-based agents or automations
• Python proficiency and a track record of connecting AI to external systems: CRMs, APIs, customer data, and operational tools
• The discipline to define what success looks like before you start building — and an eval framework that catches problems before your users do
• A genuine curiosity about Customer Success workflows and customer problems, not just the technical challenge
• Intellectual honesty about what AI can and can't do well — and the judgment to design guardrails and fallback paths accordingly
• 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
• Experience in a B2B SaaS environment

Nice to Haves

• Direct experience with Anthropic Claude or similar LLM APIs
• A background working with or alongside a Customer Success or Revenue Operations team
• Experience building regression test suites or eval frameworks for non-deterministic AI systems
• Familiarity with Salesforce, Gainsight, or similar CRM and Customer Success platforms

Benefits

• Performance-based bonus/variable pay
• Equity (for eligible roles) in a high-growth public company
• A flexible, employee-led remote model
• A professional development stipend
• Comprehensive health and parental leave plans
• Remote work where it aligns with operational requirements