Senior AI Product Engineer

Location: Austria, 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

• 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.
• Turn ambiguity into leverage: clarify the problem, make good decisions, and create systems that make future work faster.
• Help improve engineering standards, product quality, and team velocity.
• Contribute across the stack when needed, including customer-facing React product surfaces.

What We're Looking For

You may be a fit if you are:

• A strong backend engineer with excellent product judgment.
• Comfortable designing systems, data models, APIs, and relational database-backed applications.
• Experienced with LLMs or applied AI systems in real products, not just demos.
• Able to reason about AI task performance, evaluation, quality, reliability, latency, and cost.
• Comfortable working across the stack, including frontend product work when needed.
• High-ownership and comfortable operating without a fully specified roadmap or PM-written tickets.
• Good at learning unfamiliar domains quickly.
• Opinionated in the right way: you care about craft and quality, but you also know how to ship.
• Able to make thoughtful decisions from company objectives, customer insights, constraints, and strategy.
• Excited to create leverage for yourself, the team, and the product.
• Comfortable working with technologies like TypeScript/React, Python/Postgres, and Kubernetes/AWS - or able to ramp up quickly.

The best people for this role will probably describe themselves as product engineers first. AI is a major part of the work, but customer value and product quality come first.

We care less about formal titles or years of experience than about judgment, ownership, learning speed, and the ability to make the future faster.

This May Not Be the Role for You If

• You need a PM or founder to define the work before you can make progress.
• You prefer implementing clearly specified tickets over owning open-ended problems.
• You are primarily interested in ML research, model training, or fine-tuning.
• You are excited by AI prototypes but not by production reliability, evals, edge cases, and product UX.
• You are weak on backend architecture or data modeling.
• You optimize for fast output while creating technical or product debt that slows the team down later.
• You focus on solutions before deeply understanding the problem and desired outcome.

How We Work

We are remote-first and hire in Austria. The team meets in person roughly once per quarter at offsites.

Sluicebox is small, fast-moving, and highly collaborative. Engineers have a lot of agency and are expected to contribute to product direction, technical direction, and company learning.

We value:

• Drive Clarity - clarify messy problems and make good decisions.
• Extreme Ownership - own outcomes, not just tasks.
• Bias for Action - move quickly, learn quickly, and avoid unnecessary complexity.
• Raise the Bar - improve the quality of the product, codebase, and team.
• Delight & Earn Trust - build things customers and teammates can rely on.

We use AI heavily where it makes sense - in the product, in internal workflows, and in how we work as a team. Customers already pay for AI-powered capabilities in Sluicebox, and we are continuing to push further.

What Success Looks Like

In your first few months, you will have:

• Shipped meaningful product improvements with a high degree of independence.
• Built strong context on our customers, domain, product, and technical systems.
• Improved the quality, reliability, or evaluation of AI-powered workflows.
• Earned trust as someone who can operate in ambiguity and make good product and technical decisions.
• Created leverage that makes future product and engineering work faster.

Why Join

You will join a small team where exceptional engineers can have unusually high impact.

You will work on hard, real-world product problems at the intersection of sustainability, manufacturing, complex data, and applied AI. You will help turn manual, expert-heavy workflows into scalable systems that manufacturers can trust for consequential decisions.

If you want to own problems rather than tickets, build AI-native product systems, and turn ambiguity into leverage, we would love to talk.