2 months ago
Base Salary
$156k - $231k/yr
Responsibilities
- Partner with account leads and customer technical teams to scope and architect data sources, system architecture, and production delivery plans.
- Embed with customer data and engineering teams remotely and on-site to integrate cloud and data platforms.
- Build production-grade data pipelines and model messy enterprise data into trustworthy data products.
- Design and ship production 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 developer tooling to measure accuracy, hallucination rate, latency, and cost.
- Create clean interfaces and reusable building blocks instead of one-off customer code.
- Feed field learnings into platform improvements and deploy those improvements to future customers.
Requirements
- At least 3 years of experience building production software and data systems.
- Strong production-grade coding ability and the ability to architect and implement solutions for ambiguous problems and messy data environments.
- Hands-on experience building and evaluating production LLM and agent systems, including retrieval/RAG and tool use.
- Experience building and operating data pipelines, modeling enterprise data, and working with a modern cloud data platform such as Databricks, BigQuery, or Snowflake.
- Ability to work directly with customer engineering and data teams, run working sessions, explain technical decisions, and build trust through delivery.
- Comfort switching between customer-facing deployments and reusable infrastructure development.
- Willingness to travel to customer sites regularly, approximately 10–20%.
- Experience in grocery, retail, or supply chain data domains is preferred.
- Experience with knowledge graphs, ontologies, semantic layers, graph or vector stores, hybrid search, MCP, agent frameworks, MLOps, model serving, or LLM observability is preferred.
- Prior forward-deployed, solutions, implementation engineering, or early-stage startup experience is preferred.
Benefits
- Hybrid role based in the San Francisco office, with two days per week in-office.
- Regular travel to customer sites, approximately 10–20%.
- 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.
- The position is not eligible for company sponsorship.
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.