Afresh - Senior Support Engineer I

• A typical week might involve building an agentic AI support workflow in Stylo, shipping a Claude skill that lets Tier 1 Support resolve issues with a new product feature, coordinating a team-wide investigation of data issues across 200 products, and then presenting the root cause analysis and measured impact of that investigation to Product and Data Engineering leadership. Specifically, you will: • Own our most complex escalations end to end — data mapping defects, recommendation and forecast anomalies, and integration or data-feed failures • Identify and lead large initiatives that deliver critical impact against department-level OKRs, such as raising our ticket deflection rate, reducing average handle time, or reducing escalations to cross-functional teams. You will work autonomously — scoping the work yourself, defining what success looks like, and communicating progress and blockers without being asked • Define and report the numbers that prove impact: baseline before you build, quantify after, and publish on a regular cadence in channels where the appropriate teams and leaders can see it • Build the tooling that removes the work — SQL and Python, Databricks and Looker dashboards and notebooks, Stylo workflows, Claude and Cowork skills, and lightweight automations that take manual effort off Tier 1 Support and Operations • Drive cross-functional change with teams that don't report to you, partnering with Solutions Engineering, Data Engineering, Product Engineering, and Operations to fix the systems generating ticket volume — securing shared ownership, holding regular communication cadence, and raising flags visibly when progress stalls • Multiply the team rather than absorb its hardest work: mentor Tier 1 and Tier 2 engineers, lead training, and write the playbooks and source-of-truth documentation that let others resolve what only you can resolve today • Be visible outside Support — present in Tech Demos, post data-driven updates in company-wide channels, join account reviews, and represent Support in cross-functional forums • Master partner-specific behavior across our retailers and their banners, and serve as the escalation point when a judgment call needs to reach Product, Engineering, or the customer directly • What Will Make You a Great Fit • The following represent attributes our ideal candidate possesses. We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria. • 5+ years in technical support engineering, solutions engineering, data engineering, or a comparable role where you personally owned root-cause analysis on production data • Advanced SQL. You reason comfortably about joins across large, imperfect datasets, and you validate findings against the authoritative source rather than the most convenient table • Demonstrated ability to own complex cross-functional initiatives end to end and land them — including the uncomfortable parts: securing commitments from other teams, absorbing friction, and driving to a decision • A measurement instinct. You define success numerically before you start, and you speak to results rather than activity • Proficiency building with AI tools such as Claude or other agentic platforms, paired with sound judgment about where automation can be trusted and where it cannot • Scripting ability in Python or similar to automate investigation and data work • Clear, calm written communication, and the instinct to teach rather than correct when helping less experienced teammates • Comfort with ambiguity and a bias toward shipping an imperfect, iterative solution over waiting for a complete one • Self-direction. You source your own answers, set your own milestones, and do not need oversight to make progress