AI Engineer, Customer Success

Overview

AI Engineer embedded in Commercial Customer Success, building agentic LLM-based solutions across design through deployment and ongoing maintenance.

What you'll do

• Design agent architectures and prompts for customer-facing AI agents.
• Integrate agents with external systems (e.g., Salesforce, Samsara platform, Customer Success tools) and write maintainable Python code.
• Define success criteria and evaluation frameworks, then build automated test suites for real-world scenarios and edge cases.
• Own deployment, versioning, and rollback plans; ensure agents are production-ready.
• Monitor production performance (accuracy, latency, failure rates, and customer outcomes) and detect drift.
• Continuously maintain and iterate agents as products and Customer Success playbooks evolve.

What you'll need

• 3+ years of software engineering or technical experience.
• At least 1 year hands-on working with LLMs or AI agents in a production environment.
• Python proficiency and experience connecting AI to external systems (CRMs, APIs, customer data, operational tools).
• Ability to define what success looks like before building, including an evaluation framework.
• Curiosity about Customer Success workflows and customer problems.
• Judgment to design guardrails and fallback paths for AI limitations.
• Experience in a B2B SaaS environment.

Details

• Remote work open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area.
• Annual base salary range: $105,910–$160,200 USD.