Senior Support Engineer

• As a Principal Support Engineer at Afresh, you are the person who understands how our platform actually behaves for our grocery partners
• You have deep technical support, solutions, or data engineering experience, you communicate with equal clarity to a store director and a staff engineer, and you are excited to reduce fresh food waste in the grocery industry
• Support Engineering is the complex technical investigation arm of our Support organization — the last stop for internal escalations to resolve customer-facing problems across all Afresh products
• You will own the complex escalations that others cannot resolve and then work upstream to eliminate or minimize future recurrence; quantifying impact, building tooling and agentic AI workflows to deflect future volume, and then proactively driving the cross-functional efforts to eliminate the root cause
• This is a senior individual contributor role, and the scope of this role is deliberately broad
• You will be handed goals rather than tasks and you are expected to quickly and autonomously develop deep expertise across our products and the complex data relationships behind them
• You will own and lead initiatives from end to end, building influence and alignment with other teams to achieve your goals
• 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
• 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

Benefits

• Comprehensive health plans
• Generous parental leave
• Equity packages
• 401k matching
• Flexible vacation policy
• Professional development program
• Work from home stipend

• 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
• 5+ years in technical support engineering, solutions engineering, data engineering, or a comparable role where you personally owned root-cause analysis on production data
• 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
• Self-direction. You source your own answers, set your own milestones, and do not need oversight to make progress
• 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
• Clear, calm written communication, and the instinct to teach rather than correct when helping less experienced teammates
• 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
• Scripting ability in Python or similar to automate investigation and data work
• A measurement instinct. You define success numerically before you start, and you speak to results rather than activity
• Comfort with ambiguity and a bias toward shipping an imperfect, iterative solution over waiting for a complete one
• A track record of mentoring engineers and raising the technical bar of a team
• Experience supporting ML-driven products, and the ability to distinguish whether an anomaly originates in data inputs, model behavior, or application logic
• Experience with Databricks, Zendesk, Stylo, or workflow automation platforms
• Grocery, retail, or supply chain domain knowledge — hands-on familiarity with ordering, replenishment, assortment, or fresh department operations is a significant advantage