2 months ago
Base Salary
$169k - $273k/yr
Responsibilities
- Partner with account leads and customer technical teams to scope and architect data sources, system architecture, and production plans.
- Embed with customer data and engineering teams remotely and on-site to integrate cloud and data platforms and build production data pipelines and trustworthy data products.
- Design and ship production-grade LLM- and agent-powered systems, including retrieval, agentic workflows, data-quality agents, and analytics agents.
- Harden field solutions into shared platform capabilities, including knowledge graphs, ontologies, retrieval, agent frameworks, and serving infrastructure.
- Build evaluation, tracing, and development tooling to measure accuracy, hallucination rate, latency, and cost.
- Create clean interfaces and reusable building blocks instead of one-off customer implementations.
- Transfer field learnings into platform improvements and deploy those improvements to subsequent customers.
Requirements
- At least 5 years of experience building production software and data systems.
- Strong production-grade coding skills and the ability to architect and implement solutions for ambiguous problems and messy data environments.
- Hands-on experience building production LLM and agent systems using retrieval or RAG and tool use, with quality evaluation beyond manual inspection.
- Strong data-engineering experience building and operating pipelines, modeling enterprise data, and using modern cloud data platforms such as Databricks, BigQuery, or Snowflake.
- Ability to work across customer-facing delivery and reusable infrastructure development.
- Comfort collaborating with customer engineering and data teams, leading working sessions, explaining technical decisions, and building trust through delivery.
- Willingness to travel regularly to customer sites, approximately 10–20%.
- Preferred experience in grocery, retail, or supply chain data domains.
- Preferred experience with production knowledge graphs, ontologies, semantic layers, graph and vector stores, hybrid search, MCP or similar protocols, agent frameworks, MLOps, model serving, and LLM observability.
- Prior forward-deployed, solutions, implementation-engineering, or early-stage startup experience is a plus.
Benefits
- Hybrid role based in the San Francisco office, with 2 days per week in-office.
- Comprehensive medical, dental, and vision coverage with most premiums covered, plus mental health support and counseling.
- Meaningful equity for U.S. employees and a 401(k) program with company match.
- Home office stipend and coworking wallets.
- Annual professional development budget.
- Monthly wellness/lifestyle and telecommunications stipends.
- Flexible paid time off.
- Full-time U.S. employees are eligible for the listed benefits.
Tech Stack
DatabricksGoogle BigQuerySnowflake
Categories
About Afresh
Afresh is the AI platform for Grocery — built for how grocery actually operates, from the fresh perimeter to center store and retail to distribution centers. The Afresh platform helps grocers make smarter decisions about what to buy, order, produce, and sell across the entire operation, delivering higher profits, less waste, and fresher food on the shelf. Founded in 2017 with the mission to eliminate food waste and make fresh food accessible to all, Afresh today supports more than 12,500 departments across 40 states, partnering with Albertsons Companies, Stater Bros., Meijer, Wakefern, and more. Learn more at www.afresh.com.