Senior Support Engineer I

present of AI; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work in US

Job summary

Afresh is seeking a Senior Support Engineer (Remote, United States) within Support Engineering. This senior individual contributor handles the toughest escalations, digs into production data to map errors, odd forecasts, and broken data feeds, and pushes other teams to fix the source so tickets stop recurring.

A strong candidate brings advanced SQL, Python scripting, and years of hands-on investigation experience.

Qualifications

• Strong SQL skills with experience on messy production data.
• Hands-on investigation across data, model and app logic.
• Proficiency in Python scripting for data analysis.

Responsibilities

• Dig into root causes in production data for hard escalations.
• Coordinate with multiple teams to fix source data issues.
• Mentor colleagues and document findings for engineering audiences.
• Develop Claude-based automated workflows to reduce repeat tickets.

Skills

Advanced SQL

Python scripting

Investigation experience

Root cause analysis

Claude workflows

Tools

Claude

Job description

Customer & Solutions · Remote - United States · Senior level

This is a senior individual contributor role inside Support Engineering, the group that takes the hardest escalations from other support tiers. The work is to dig into root causes in production data, such as mapping errors, odd forecasts and broken data feeds, then push other teams to fix the source so tickets stop coming back. A strong candidate brings advanced SQL, Python scripting, several years of hands‑on investigation experience, and the patience to win agreement from teams they do not manage.

How it fits the AI era

AI changes this work by letting one person build automated support workflows and reusable Claude skills that handle routine issues, so the team spends less time on repeat tickets. The role also involves telling apart whether a strange result comes from the data, the model, or the app logic, and that judgment still needs a person. Deciding where automation can be trusted, explaining findings clearly to store and engineering audiences, and mentoring colleagues stay human work.

How it builds AI experience

Someone in this role would build agentic support workflows and Claude based tools for a company whose product forecasts demand and writes grocery orders, and would see how an ML product behaves when its inputs go wrong. To prepare, practice building small automations with Claude or similar tools, and learn to trace a strange forecast back to its source data. Measuring how much work each tool removes is a good habit to build early.

Worth showing

• Advanced SQL on messy data
• Root cause analysis write-ups
• Claude or agentic workflow projects
• Measured impact of past initiatives

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Afresh

An AI operating system for grocery fresh departments that forecasts demand and writes purchase orders, aimed at cutting food waste and shrink.