Product Support Engineer

• A builder. When you solve the same problem twice, you script, automate, or build something so no one solves it a third time - and you can show us what you’ve built \n

• AI-forward. You reach for AI tools by default and use them for real work: prompt design, AI-assisted troubleshooting, automated workflows \n

• Technically fluent. Comfortable reading/writing basic scripts and queries (Python, JavaScript, SQL, JSON), working with REST APIs, and reading logs and payloads without flinching \n

• Analytical. You bring the pattern, the count, and the cost - not just the anecdote \n

• An excellent communicator. Crisp, kind writing that makes technical problems simple for a stressed customer \n

• Proven under volume. Experience in a high-volume, direct-customer technical support environment \n

• Owner’s reflexes. Bias toward action, comfortable with ambiguity, willing to be part of an on-call rotation \n

• 2+ years in technical support, solutions engineering, or a similar customer-facing technical role (floor only - the builder bar governs) \n, * Experience with Intercom-class ticketing platforms, especially with AI agents deployed; Salesforce, Jira

We’re representing a fast-growing Series C B2B AI/SaaS company modernizing a critical piece of global commerce infrastructure - doubling revenue year over year.

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• Support here is technical, production-critical work: when a transaction fails, a customer’s operations are stuck, and they need someone who can read the error, trace the root cause, and fix it - fast and kindly \n

• You’ll triage and resolve tickets directly - but the real job is what you do with ticket two: script it, automate it, document it for the AI, or drive the product fix so it never happens again \n

• You’ll work with an AI-first support stack, partnering directly with R&D to turn proven AI-assisted resolutions into automated workflows and durable product fixes \n

• As AI containment climbs, this role grows with it - into AI operations, knowledge management, or support automation \n

• The honest answer to “will AI take this job”: this job runs the AI \n

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What you’ll do

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• Review, triage, and resolve inbound customer issues within SLAs - with AI tools accelerating your root-cause analysis, not replacing your judgment \n

• Eliminate ticket categories at the source: scripts, automations, AI-structured articles, error-message fixes, self-serve tooling \n

• Build and maintain AI workflows with R&D, turning proven resolutions into automation the AI can execute safely \n

• Spot patterns and quantify them - which issues generate the most tickets, what they cost, what would eliminate them - and bring that data to Product \n

• Advocate for the customer internally; escalate urgent production issues with real ownership \n

• Become a product and domain subject-matter expert (we’ll teach you the domain - see below) \n

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What good looks like

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• 90 days: resolving independently across ticket segments; first automation or AI workflow shipped; first knowledge article written so the AI can answer it going forward \n

• 12 months: owns one of the team’s specialization areas (AI operations, knowledge, or automation); can point to ticket categories that no longer exist because of you \n

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