Location: Austin, TX or LATAM, remote-first Type: Full-time Team: Engineering / Product

About Sluicebox

Our mission is to enable the world to invent and build better products.

Sluicebox is building autonomous AI systems that help manufacturers understand, report, and improve the environmental impact of complex products, starting with electronics and carbon. Today, manufacturers use Sluicebox to scale work that is otherwise manual, expert-heavy, and hard to trust: carbon/LCA analysis, supplier data collection, compliance responses, and product sustainability decisions.

We are building toward AI agents that can enrich, analyze, and reason over complex product, component, supplier, and sustainability data - helping manufacturers make better decisions faster.

We are a small, high-ownership team where engineers do not just implement features. They help define the problems, shape the solutions, and build the systems that make the company faster over time.

The role

We are looking for a Senior AI Product Engineer: a product-minded, backend-strong software engineer who can build reliable AI-powered product systems.

This is not an ML research role. We are not looking for someone whose primary interest is training models or doing academic machine learning. We are looking for a strong software engineer who can use LLMs, agents, evals, product judgment, and thoughtful system design to solve real customer problems.

You will work on ambiguous, high-value problems across product, backend systems, and applied AI. Discovery and delivery are both part of the job: spending real time with customers and their data, testing assumptions early, and shipping work that earns its place.

Some of the most important work will involve automating carbon/LCA methodology and enrichment, improving the accuracy and trustworthiness of AI outputs, and turning repeated manual workflows into scalable product systems.

You should be excited by messy real-world data, complex customer workflows, and the challenge of building AI systems that customers can actually rely on.

What you’ll do

You will:

• Own ambiguous product and technical problems end-to-end, from understanding the customer need to shipping and iterating on the solution.
• Build backend-heavy product systems that handle complex product, component, supplier, and sustainability data.
• Design and improve AI-powered workflows using LLMs, agents, structured context, tool use, and evaluation loops.
• Work on accuracy, trust, explainability, and reliability of AI outputs in customer-facing and internal workflows.
• Spend real time with customers and their data to understand what is worth building.
• Collaborate closely with founders, product, engineering, and domain experts to make good product and technical tradeoffs.