Job Description
About Karbon Karbon is the global leader in AI-powered practice management software for accounting firms. We provide an award-winning cloud platform that helps tens of thousands of accounting professionals work more efficiently and collaboratively every day. With customers in 40 countries, we have grown into a globally distributed team across the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, growing rapidly, and have a people-first culture that is recognized with Great Place To Work® certification and on Fortune magazine's Best Small Workplaces™ List. About the Role As a Senior Support Engineer at Karbon, you sit at the deepest tier of our engineering support function. You are the last line of investigation before an issue reaches a product engineering team, and you take genuine ownership of the cases that reach you. Your work is a mix of deep technical diagnostic, production data operations, and clear cross-functional communication. Our T3 function operates on a few core principles: quality of investigation over reactive throughput, durable fixes over repetitive patches, safe production access with strong governance, and knowledge treated as infrastructure. We expect Senior Support Engineers to embody these principles in how they work and to raise the bar for the engineers around them. This role works roughly US Pacific hours to provide coverage for our North American customer base and is only open to candidates located in Pacific Time Zone. As a Senior Support Engineer, you will... Lead root cause analysis on highly complex issues: Take ownership of escalations that require structured RCA, isolating issues to specific services, workflows, or data states. You are comfortable resolving highly complex issues in familiar systems and medium complexity issues in unfamiliar ones, and you can articulate the why, not just the what. Read the source: Read C# and the broader .NET stack well enough to follow application logic, trace through a method, and pinpoint where behaviour diverges from expectation. You are not expected to ship production code, but you are expected to understand it. Write safe, considered SQL: Diagnose data-layer issues by writing and reviewing SQL against production-shaped data. Design safe remediation plans, anticipate downstream implications, and create reusable stored procedures for recurring intervention patterns. Make sound production access decisions: Operate within our production safety guardrails, evaluate trade-offs on higher-risk interventions, and review remediation plans before they execute. You model the behaviour you want to see across the function. Investigate and reproduce defects across the platform: Use logs, telemetry, API behaviour, and environment replication to confirm whether something is a bug, a misconfiguration, or a workflow issue, and document your findings so an engineer can act on them. Monitor and respond to production alerts, looping in additional engineers and stakeholders as needed. Create well-scoped tickets: When a confirmed bug or product gap warrants engineering attention, you write the ticket. A clear problem statement, reproduction steps, affected scope, and enough context that an engineer can pick it up and begin work. Lead technical investigations during incidents: Act as a trusted contributor during moderate to high severity incidents, establishing timelines, synthesising signal, and where appropriate mitigating independently when Engineering is unavailable. Uplift escalation quality across tiers: Review and feed back on tickets from T2, raise the bar for investigative clarity, and surface recurring themes with structured evidence so they can be addressed systemically rather than case by case. Build reusable automation and tooling: Identify repetitive investigation or remediation work and replace it with scripts, stored procedures, or lightweight tooling. Reduce the team's reactive load over time. Mentor peers and the broader Support function: Mentor T2 engineers and your T3 peers, share what you learn, and contribute to team-level standards. You raise the technical bar by example and through coaching, not just by being good at your own work. Communicate complex issues clearly to customers and internal stakeholders: Confidently lead live troubleshooting calls when required, write clear customer-facing updates, and translate technical complexity into messaging that lands with the audience in the room. Use AI as an accelerator of judgment: Apply AI tooling to refine investigative approaches, validate hypotheses, detect patterns across case data, and improve documentation. AI is an accelerator of your expertise, not a substitute for it. About You You have 5+ years of experience in technical support engineering, application support, or a closely related role in B2B SaaS, with meaningful time spent at the deepest tier of investigation. You write SQL confidently and safely. You can read exec