Staff Forward Deployed Engineer
A
AfreshGrocery AI
San Francisco, CA (hybrid, 3 days/week onsite preferred) or Remote in approved U.S. states. ... reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WIFull-TimeStaff
SalarySalary Band in U.S. (USD): $168,912-$253,368 + meaningful early-stage equity + benefits
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Job Details
- Experience
- 4+ years of experience building software professionally
- Required Skills
- AzureData engineeringData sciencedbtDatabricksPySpark
Requirements
- Have 4+ years of professional software-building experience.
- Bring depth in at least one of backend or full-stack engineering, data engineering, data science, or AI engineering, with willingness to work across the others.
- Have customer-facing delivery experience in consulting, forward-deployed, solutions, or implementation work.
- Be able to turn a vague problem into a scoped plan through discovery and questioning.
- Explain technical tradeoffs to engineers and business leaders.
- Learn unfamiliar systems quickly, including ERP, merchandising tools, or data warehouses.
- Use AI tools to build effectively and have shipped an AI-enabled product or workflow.
- Understand where AI systems are useful, how they fail, and how to evaluate their quality.
- Be comfortable traveling regularly to customer sites (~10–20%).
- Nice to have: cloud data platform experience, particularly Databricks, Azure, PySpark, or dbt.
- Nice to have: production LLM or agent systems with a method for measuring quality.
- Nice to have: grocery, retail, or supply chain experience; production knowledge graphs, semantic layers, or retrieval systems; or experience leading engineers through design reviews, standards, or mentorship.
Responsibilities
- Work with customer business and technical teams to scope problems, identify users and available data, define success, and establish what will not be built.
- Surface undisclosed data, process, and security constraints, and challenge requests that will not achieve the desired result.
- Design and build solutions on Afresh's platform, including data pipelines, integrations, agents, workflows, and user-facing applications.
- Put working pilots in front of users quickly.
- Deploy solutions in customer environments with customer engineers and Afresh's platform team.
- Observe usage, verify answer quality, and iterate until the solution is part of the customer's workflow.
- Bring field learnings to the platform team and help determine what should become platform functionality versus custom work.
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