Forward Deployed Engineer
$150k - $250kGuac
Forward Deployed Engineer
At Guac, we're solving grocery food waste with AI. We forecast exactly how much of each product will sell, helping grocery retailers order and produce the perfect amount of inventory — and we're building AI-native tools that put those forecasts directly into the hands of store operators and buyers.
The grocery industry is enormous (it accounts for 4% of GDP) — and grocery food waste is a huge cost to grocers' bottom lines, but also to our planet.
Today, we're working with major supermarket chains in the US and Canada, and we've scaled to 7-figures in ARR. We're backed by leading investors including Y Combinator, 1984 Ventures, Collaborative Fund, and angels from Open AI, Instacart, and Citadel Securities.
We've brought together an exceptional team from Palantir, BCG, Oxford, Cambridge, and MIT to solve intellectually challenging problems and tackle food insecurity and waste with technology.
We're looking for talented forward deployed engineers in NYC to join our mission.
About the Role
As a Forward Deployed Engineer at Guac, you'll be the technical bridge between our products and our customers. You'll work directly with grocery retailers — from their IT teams to their store operators — to deeply understand their business, integrate with their systems, and ship custom solutions that make our products work for them.
This isn't a role with tightly-scoped tickets. You'll own customer deployments end-to-end: scoping the integration, building the data pipelines, extending the recommendation engine, and standing alongside customers as we roll out across hundreds of stores. We're looking for engineers who can hold their own in a technical deep-dive with a customer's IT team in the morning, ship production code in the afternoon, and work on our products.
Your responsibilities will include:
Customer & Deployment
- Collaborate directly with customers' technical teams to understand their IT infrastructure and integrate with their internal data systems
- Work with customers' supply chain and store operations teams to translate their unique business logic into code
- Own the end-to-end success of customer deployments, from kickoff through scaling across hundreds of stores
- Be the technical face of Guac on the ground — building trust, debugging live, and turning customer feedback into product
Data & Backend
- Design and build ETL pipelines that process billions of rows of data multiple times per day across customers, using Python, Dagster, and Pub/Sub
- Build and extend backend services (Python/FastAPI) that power our ordering and production planning products
- Extend our recommendation engine to meet the business needs of each new customer
- Expose our data and systems to LLMs via MCP servers, tool-use APIs, and similar protocols
About You
- 3+ years of relevant software engineering experience
- Strong proficiency in Python and SQL
- Proven experience designing and implementing ETL systems across large distributed datasets (Dagster, Airflow, or similar)
- Excellent communication skills and a commercial mindset — you've worked directly with customers and can hold your own in a room with both engineers and supply chain VPs
- Comfortable operating with ambiguity and minimal process — you thrive when given a problem and trusted to figure out the solution
- AI-native: you use Claude Code, Cursor, or similar AI coding tools daily and ship significantly faster because of it
What We Offer
- First-hand experience building an early-stage startup with real product ownership
- Compensation: $150k–$250k base + competitive equity
- Fully employer-paid healthcare (medical, dental, and vision)
- Unlimited vacation days
- Fully covered food expenses in the office (lunch/dinner)
- Free Equinox membership
Our Tech Stack
- Languages & Frameworks: Python, FastAPI, SQL
- Data & Pipelines: Dagster, Pub/Sub, BigQuery, Postgres, Dask
- Cloud & Infrastructure: GCP, Terraform, Docker
- AI: MCP servers, Anthropic/OpenAI APIs, agentic tooling
Note: this is a 5x day a week in person role in NYC
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