Design and implement LLM-powered workflows to automate finance and accounting tasks like detecting anomalies in books, scanning and categorising financial documents like invoices and credit notes.
Build benchmark/eval suites to systematically develop a system of agents to conduct accounting tasks.
Own user feedback loops and store data in a structured manner for LLM consumption.
Shape and evolve our AI stack, continuously researching and implementing the best solutions for our use cases.
Collaborate with other engineers, product and design teams to deliver seamless consumer grade experiences to customers.
Contribute across the stack to get the work done, when needed.
Requirements
Senior/Staff level engineering experience at product companies
Practical understanding of vector stores, RAG, context engineering and other techniques used in building AI agents
Strong grasp of machine learning concepts, LLMs, libraries, or frameworks commonly used in AI agent development
Understanding of how to evaluating performance and outputs of AI systems
Comfortable with working in a Go/Python codebase and cloud infrastructure (We use GCP but welcome experience in AWS/Azure)