Senior Forward Deployed Engineer

Join Afresh, a company revolutionizing the grocery industry with AI technology. As a Senior Forward Deployed Engineer, you will be at the forefront of delivering our AI solutions to enterprise grocery customers while also building the platform that enables fast delivery. You will spend dedicated time in the field, working closely with customers, and dedicated time on the platform, turning field learnings into reusable tooling. This is a senior, hands-on role that requires a strong background in production software and data systems, as well as comfort working with customers and their technical teams.

• Partnership with Afresh's account lead and the customer's technical teams to scope and architect the work, including data sources and architecture.
• Integration with the customer's data and engineering teams to build production-grade pipelines and model messy enterprise data into trustworthy data products.
• Ownership of the flywheel, ensuring that field learnings flow straight into the platform, and platform improvements show up at the next customer.
• Real data-engineering depth: building and operating data pipelines, modeling messy enterprise data, and working in a modern cloud data platform (Databricks, BigQuery, Snowflake, or similar)
• An architect's instinct: you can take an ambiguous problem and a messy data landscape, design a clean and workable solution, and then build it
• Genuine AI/LLM depth — you've built real systems with LLMs and agents (retrieval/RAG, tool-use) and you evaluate quality rather than eyeball it
• Range across both modes — you genuinely like being in front of customers and going heads-down to build reusable infrastructure, and you can switch between them without one suffering. This is the role's defining trait
• Customer-facing comfort: you work well with a customer's engineers and data teams — running working sessions, explaining your thinking, and earning trust through what you deliver
• We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria
• 3+ years building production software and data systems, with strong, production-grade code
• A bias toward ownership and momentum, and comfort traveling to customer sites regularly (~10-20%)
• Experience in grocery, retail, or supply chain data domains
• Knowledge graphs, ontologies, or semantic layers in production; graph and vector stores (pgvector, Pinecone, Weaviate) and hybrid search
• MCP or similar tool/context protocols; agent frameworks (e.g., LangGraph); MLOps, model serving, and observability for LLM systems
• Prior forward-deployed, solutions, or implementation engineering — or early-stage startup experience navigating rapid customer expansion