Software Engineer, AI

From volatile markets to climate shifts, independent operators face mounting pressure. While sustainable investments often yield the best long-term returns, they require financial clarity and capital that fragmented legacy systems can’t provide.

Ambrook is building a world-class team to empower farmers, ranchers, and small-business owners using modern AI tools. You’ll shape how we use LLMs and intelligent systems to make messy, high-stakes financial workflows faster, smarter, and more accessible for users across the country.

We’re shipping features across the financial landscape, from better receipt parsing and review to auto-categorization to intelligent conversational AI features that let people get a deeper understanding of their books and their business with fewer clicks. We’ve got a big vision of making AI work for real family businesses, not just mega-corps. If you’re interested in building with us, let’s talk.

• Build and ship a feature powered by an LLM - e.g., parsing a new type of paper document, or categorizing financial transactions.

• Review our current uses of AI and write up a note identifying where AI could meaningfully improve automation and accuracy.

• Collaborate with product and engineering to understand customer workflows and where AI would reduce manual pain.

• Establish early foundations for evaluation pipelines, prompt management, and feedback loops to improve LLM performance over time.

• Implement or improve systems for document extraction and financial transaction tagging, using both heuristics and model-based approaches.

• Collaborate closely with design and product to make AI features feel reliable, intuitive, and helpful, not mysterious or brittle.

• Architect and scale systems for automated bookkeeping and analysis using hybrid AI + rule-based systems.

• Contribute to our long-term AI strategy: which tasks to automate, how to measure confidence, and when to keep a human in the loop.

• Help build internal tooling for prompt iteration, embedding search, labeling, and retraining.

• Share learnings in a post on Ambrook Research or an open-source tool that helps others tackle similar messy real-world data problems.

• You've built and shipped ML/AI-driven features, ideally with LLMs, in a product that’s in production, not just in a notebook.

• You're excited to apply language models to real-world, unstructured, often ugly datasets, and turn them into valuable product experiences.

• You're pragmatic about AI: you know when to use an LLM, when to write a regular expression, and when to ask the user.

• Next.js / React application written in Typescript

• Hosted on Google Cloud

• Firestore & Google Cloud Storage for data storage

• BigQuery & Data Studio for data insights

• Real Talk – We create space for ourselves and others to be straightforward, vulnerable, and accountable.

• Reach Understanding – We are driven by curiosity and empathy to learn about our customers, team, and world.

• Be Proactively Resourceful – We are internally motivated and externally empowered to identify opportunities and solve problems.

• Derisk Thoughtfully – We lean into the biggest risks we face as a company and put in the work to address them systematically.

• Find the Positive-Sum – We believe in creating incentive structures that align the needs of our company, our customers, and our planet.

• Ambrook is an equal opportunity employer. We are committed to building diversity and inclusion into our core company culture.