Support Engineer

About the Role Our Engineering and Support organizations are rapidly evolving toward an AI-first operating model. We actively use Claude as a core development and troubleshooting partner and are adopting the AI-Driven Lifecycle (AI-DLC) across our teams. For Support, this means we are shifting from manual ticket triage and one-off fixes toward AI-assisted investigation, reproducible remediations, and durable improvements that prevent the next ticket. If you’re excited about working at the intersection of customer impact, deep technical investigation, and next-generation AI-assisted problem solving, this role is for you. Role Summary The Support Engineer is the technical backbone of our customer support escalation path. When an issue is reported to Tier 1 Support and they are unable to resolve it, it is escalated to you. You have direct access to the production database and the source code, and you are expected to solve problems at a level of sophistication well beyond surface-level configuration. You will diagnose issues by reading code, querying data, and reproducing problems in lower environments. You will apply data fixes where appropriate and contribute code changes back into the product codebase to permanently resolve recurring issues. When a problem requires deeper architectural change or sits clearly inside a product team’s area of ownership, you will partner with and escalate to the Engineering team responsible for that area. Additionally, you will be the technical expert who works with customers and third parties to implement API integrations, educate interested parties on data integration and reporting, and provide technical solution guidance. This role sits between Tier 1 Support and Engineering. You are the person who turns “something is broken” into either a verified fix, a defensible data correction, or a precise, reproducible escalation that engineering can act on immediately. Key Expectation Support Engineers are expected to leverage AI tools (e.g., Claude) as a primary partner for log analysis, code reading, query construction, fix authoring, and customer communication, while maintaining full ownership of correctness, data integrity, and customer outcomes. What You’ll Do Tier 2 Issue Resolution Own escalations from Tier 1 Support: take in the ticket, reproduce the issue, and drive it to resolution. Investigate issues by reading product source code, tracing requests across services, and inspecting production data. Author and apply targeted data fixes against the database when an issue is data-related, following safe-change practices (review, backup, rollback plan). Contribute code changes into the product codebase to fix defects you have diagnosed, with appropriate tests and review. Determine when an issue exceeds Tier 2 scope and escalate to the responsible Engineering team with a clear reproduction, root-cause hypothesis, and supporting evidence. AI-Driven Investigation & Remediation Use Claude and other AI tools as a primary interface for log triage, stack trace analysis, query drafting, and code-change generation. Apply AI-DLC practices: structured prompting, iterative refinement, validation loops, and review of AI-generated SQL and code before it touches customer data. Continuously improve personal and team-level AI playbooks for the most common escalation patterns. Shift effort from repetitive manual triage to problem framing, hypothesis testing, and validation of AI-generated output. Customer Impact & Communication Partner with Tier 1 Support, Customer Success, and customers directly when needed to confirm symptoms, validate fixes, and communicate status. Translate technical findings into clear, non-defensive customer-facing explanations. Maintain ownership of escalated tickets through resolution, including verification with the reporter. Technical Guidance and Solution Design Provide partners and customers with API usage and integration guidance. Work with internal solution designers to ensure correct workflow implementations and to identify gaps/best practices. Ensure that documentation for integration tools and techniques is maintained and kept up to date. Codebase & Data Stewardship Work within large, existing codebases—making them more observable, debuggable, and resilient as a side effect of resolving real customer issues. Treat every escalation as a signal: identify recurring patterns and propose product fixes, monitoring, or runbook improvements. Apply database changes with discipline—scripted, reviewed, reversible, and logged. Engineering Partnership Build strong working relationships with the product Engineering teams who own each area of the platform. Hand off escalations to Engineering with reproductions, isolated test cases, and clear acceptance criteria. Feed support insights back into engineering planning to reduce future escalations. Quality & Ownership Validate AI-generated SQL and code for correctness, blast radius, and long-term maintainability before applying. Ensure code contributions include appropriate unit and regression tests. Maintain accountability for customer outcomes—not just ticket closure. Actively track and report on Tier 2 operating metrics. Required Skills & Experience AI-Forward Support Mindset Experience using AI tools (e.g., Claude, Copilot, etc.) for investigation, query writing, code generation, and customer communication drafting. Comfort generating a majority of SQL and code fixes through AI and validating/refining outputs before applying them to production. Ability to decompose ambiguous customer reports into clear hypotheses, prompts, and constraints. Technical Skills Strong SQL skills, including the ability to read and write production-grade queries against SQL Server, investigate data anomalies, and author safe data-correction scripts. Solid fundamentals in C# and .NET (all versions), enough to read existing code, trace logic, and contribute targeted bug fixes. Familiarity with Angular, Vue, and/or other modern frontend patterns sufficient to investigate UI-layer issues. Experience with REST/SOAP APIs, JSON/XML, log analysis, and system integrations. Comfort working in large legacy codebases and improving them incrementally. Working knowledge of Git-based workflows, CI/CD pipelines, and Agile delivery. Support & Engineering Discipline Strong debugging and problem-solving skills; able to reason about complex systems and trace issues across layers (UI → API → service → database). Disciplined approach to production data changes: scripted, reviewed, reversible, logged. Excellent written and verbal communication; able to explain technical findings to both customers and engineers. Calm under pressure; able to prioritize across multiple active escalations. Commitment to code quality, testing, and secure coding practices, even in fix-forward situations. Experience & Education 3+ years of experience in a technical support, application support, or software engineering role with direct customer-issue ownership. Demonstrated experience working with production databases and contributing code into a shared product codebase. Bachelor’s degree in Computer Science or related field (or equivalent experience). Why This Role Is Different You will work on real, revenue-critical systems and real customer problems—not synthetic tickets. You will have first-class access to the codebase and the database, and the authority to fix things, not just route them. You will help define how AI changes technical support in practice, moving from “closing tickets” to “engineering durable resolutions.” You will operate as a true bridge between Customer Success and Engineering, with influence on both sides. You will join a team that is actively evolving its support model—not just talking about it.