Posted 9 days ago
Description
The role asks for an engineer who can build generative AI applications for financial and legal workflows and carry models through the whole lifecycle, from experimentation and training to testing, monitoring and deployment. A strong candidate writes production Python and has deep expertise in at least one area such as retrieval, entity extraction and knowledge graphs, ranking, tabular ML or predictive modelling, with familiarity across the rest. Product sense matters too, since the work is judged by its impact on end users, and some knowledge of AWS AI tooling helps.
How it fits the AI era
This is a build role in the AI era, focused on applying current models and agentic approaches to messy debt market data and document heavy workflows. Much of the routine work of reading and structuring financial information is being automated, so the engineer spends time on evaluation, retrieval quality and turning vague problems into well scoped bets. Judgement about what to build, how to measure it and how to keep results reproducible stays human.
How it builds AI experience
The job offers hands on experience with retrieval, re-ranking, knowledge graphs and graph based retrieval, plus evaluation practice across the model lifecycle, all applied to credit data and legal documents. Building this background means working on document search and extraction projects, learning to design evals and monitor deployed models, and getting comfortable with AWS AI services. Curiosity about new research and a habit of testing ideas quickly would help.
Worth showing
- Production Python
- Retrieval and re-ranking
- Knowledge graphs and graphRAG
- Model lifecycle and evals
- AWS AI infrastructure
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About 9fin
9fin delivers debt market intelligence, news, and credit analytics powered by automated workflows, per company statements.
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