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Salary: USD 130,000 - 195,000 / annual
Afresh is an AI platform for grocery retail that helps major chains like Albertsons, Meijer, and Wakefern optimize fresh inventory, reduce food waste, and drive smarter decisions across their enterprise. The company has achieved 70% revenue growth in 2025 and now operates across 10% of the U.S. grocery market, preventing over 200 million pounds of food waste annually.
As a Senior Support Engineer, you will be the technical escalation expert who owns Afresh's most complex customer-facing problems. This is a senior individual contributor role with deliberately broad scope—you will be handed goals rather than tasks and expected to develop deep expertise across products and their underlying data relationships autonomously.
Your typical week involves building agentic AI support workflows, shipping Claude skills to empower Tier 1 support, coordinating investigations across product data issues, and presenting root-cause analyses to Product and Data Engineering leadership. You will own complex escalations end-to-end (data mapping defects, recommendation anomalies, integration failures), identify and lead initiatives that deliver critical impact against department OKRs (ticket deflection, handle time, escalation reduction), and define metrics that prove impact before and after your work.
You will build tooling using SQL, Python, Databricks, Looker, Stylo workflows, and Claude/Cowork skills to remove manual work from Tier 1 Support. You will drive cross-functional change with teams that don't report to you—Solutions Engineering, Data Engineering, Product Engineering, Operations—securing shared ownership and holding them accountable to progress. You will mentor Tier 1 and Tier 2 engineers, write playbooks and documentation, and represent Support in company-wide forums and account reviews.
This role requires mastery of partner-specific behavior across retailers and their banners, serving as the escalation point when judgment calls need to reach Product, Engineering, or the customer.
REQUIREMENTS:
- 5+ years in technical support engineering, solutions engineering, data engineering, or comparable role with hands-on root-cause analysis on production data
- Advanced SQL: comfortable reasoning about joins across large, imperfect datasets; validate findings against authoritative sources
- Demonstrated ability to own complex cross-functional initiatives end-to-end, including securing commitments from other teams and driving to decision
- Measurement instinct: define success numerically before starting; speak to results rather than activity
- Proficiency building with AI tools (Claude or other agentic platforms) with sound judgment about where automation can be trusted
- Scripting ability in Python or similar to automate investigation and data work
- Clear, calm written communication; instinct to teach rather than correct when helping less experienced teammates
- Comfort with ambiguity and bias toward shipping imperfect, iterative solutions
- Self-direction: source your own answers, set milestones, make progress without oversight
NICE TO HAVE:
- Grocery, retail, or supply chain domain knowledge (ordering, replenishment, assortment, fresh operations)
- Experience with Databricks, Zendesk, Stylo, or workflow automation platforms
- Experience supporting ML-driven products; ability to distinguish whether anomalies originate in data inputs, model behavior, or application logic
- Track record of mentoring engineers and raising technical bar of a team
