Siena AI - Technical Support Engineer

• You own complex technical issues directly with customers. You’re the technical face of Siena when depth is required. • You translate complex technical problems into clear explanations for customers and non-technical teammates. • You manage expectations confidently through multi-step debugging processes. • You escalate to Engineering only when an issue genuinely requires a code fix, infrastructure access, or schema migration. • Work at the edge of AI-native infrastructure • You support customers integrating with Siena’s AI agents across Shopify, Gorgias, Zendesk, Kustomer, Gladly, and custom environments. • You troubleshoot LLM-based agent behavior, integration edge cases, and platform failures. • You use AI tools actively in your diagnostic workflow. You’re not just supporting AI products — you’re fluent in them. • You have 1+ year of technical support at a SaaS company. You’ve owned hard technical threads end-to-end, from customer report to closed ticket, without handing the thread to engineering. • You debug REST APIs, webhooks, auth flows, JSON, and HTTP protocols. You find the break and distinguish customer-side cause from product cause. • You’re fluent in customer-side JavaScript: browser devtools, event handlers, script conflicts, timing issues. You’re comfortable using AI coding tools like Claude Code to navigate unfamiliar codebases quickly. • You write diagnostic SQL to validate data, trace ingestion paths, and answer your own data questions without waiting on a data team. • You’re comfortable with production systems: logs analysis, monitoring tools, system debugging. • AI/LLM expertise (preferred) • You have experience with LLMs, prompt engineering, or AI model integration. • You can triage AI agent behavior and distinguish a prompt/config issue from a model-level problem. • You’re familiar with how LLM-based systems fail: hallucinations, retrieval gaps, prompt sensitivity, workflow misconfiguration, Custom Action misfires. • You have experience with AI APIs (OpenAI, Anthropic, etc.). • Your written and verbal English is strong. You explain complex technical issues to non-technical stakeholders without losing them. • You build trust quickly. Customers feel like their problem is in capable hands. • Empathy and urgency coexist naturally for you. • You work independently in a remote environment with strong async communication. • Built for startup pace • You’re comfortable in ambiguity. You create structure where there isn’t any. • The leverage mindset is already a habit: when you talk about past wins, you naturally mention what you did so the next instance wouldn’t escalate — not just how you fixed the ticket. • You’ve coached or trained non-technical teammates. Pairing sessions, documentation that got used, concrete evidence of being a multiplier. • You're available to cover North America timezones • What Success Looks Like • 90 days • 90 days • Engineers are no longer pulled into support escalations. Tier 2+ resolution is yours by default. • Tier 2+ resolution time baseline is established and surfaced. • You’ve mapped the most common technical failure patterns across the customer base. • At least one Tier 2 pattern has moved back to Tier 1 with a runbook the Support team is actively using. • You’ve built a working partnership with the Support Manager and are co-prioritizing what to systematize next. • 6 months • 6 months • Resolution time is measurably improving from the 90-day baseline. • CSAT on technical issues is improving. • Engineering is fully protected from support interruptions. • The feedback loop to Engineering is running systematically — patterns, bugs, and product gaps surfaced before things break loudly. • The Support team is resolving more independently. Your internal documentation covers the most common failure modes. • You’ve shipped at least one systemic improvement project: auto-triage, observability access, or equivalent. • You’ve supported AI or LLM-based products before: hallucination patterns, prompt sensitivity, retrieval-grounded responses. • You have a background in e-commerce or DTC and understand the merchant world: catalog, orders, fulfillment, returns. • You’re familiar with modern observability tooling: Honeycomb, Grafana, Splunk, Sentry, Kibana, or equivalents. • You’ve built internal tooling or automation to improve support workflows — a triage bot, runbook generator, custom dashboard, or anything that turned a recurring manual task into a repeatable system. • You’re fluent with Claude Code or equivalent AI coding tools. Your value is judgment about when to automate and how to verify output, not syntax recall.