5 months ago
London, United KingdomSenior
Responsibilities
- Design and build generative AI applications for complex financial and legal workflows.
- Lead the end-to-end model development lifecycle, including experimentation, training, testing, evaluation, deployment, and monitoring.
- Build high-precision document extraction systems using schema-driven extraction, citation grounding, validation, and confidence scoring.
- Develop review, verification, reconciliation, retrieval, context-engineering, and data-quality workflows for long documents.
- Create labelled datasets, annotation frameworks, synthetic data, and evaluation sets for document extraction.
- Build and operate production extraction pipelines, evaluation systems, model-serving infrastructure, and monitoring.
- Collaborate cross-functionally, translate business problems into scoped initiatives, mentor teammates, and promote AI adoption across the organization.
Requirements
- Deep experience with complex legal and financial documents, including bond offering memoranda, credit agreements, indentures, court filings, and transaction documentation.
- Expertise extracting structured financial and legal information such as terms, covenants, definitions, parties, dates, thresholds, baskets, ratios, and transaction mechanics.
- Strong understanding of document structure, section hierarchies, cross-references, defined terms, tables, exhibits, and legal-document patterns.
- Experience applying LLMs to high-precision structured extraction tasks, including grounding, validation, and confidence scoring.
- Experience designing data-quality, review, verification, reconciliation, training-data, annotation, synthetic-data, and evaluation systems.
- Strong understanding of chunking, document segmentation, retrieval, and context construction for long-document reasoning.
- Familiarity with leveraged finance, debt capital markets, credit agreements, covenant packages, bond documentation, restructuring, and related legal concepts.
- Ability to build and operate production ML pipelines, evaluation systems, model-serving infrastructure, and monitoring.
- Strong proficiency in Python for production-ready delivery.
- Experience across the full model lifecycle, including experimentation, training, testing, monitoring, and deployment.
- Strong product focus and desire to understand the end-to-end impact of solutions on users.
- Good knowledge of AWS AI infrastructure.
Benefits
- Competitive salary, equity, pension contributions with employer matching, private medical insurance, paid sick leave with income protection, and group life assurance.
- Season ticket loan and Cycle to Work schemes.
- 25 holiday days per year plus local public holidays, with the option to exchange holidays for alternative days.
- Hybrid working model with flexibility over when and where to work.
- Ability to work abroad for up to three months per year.
- One month of paid sabbatical after five years of service.
- Enhanced parental leave and flexible working arrangements.
- Professional learning and development budget and an £800 annual AI experimentation budget.
- Quarterly team socials and summer and winter company events.
Categories
About 9fin
9fin builds an AI-driven intelligence platform for the global debt markets, combining real-time news, credit data, and analytics for investment banks, asset managers, advisors, and law firms. It sells subscriptions to tools that centralize deal information, public and private credit data, and workflows across leveraged finance, structured credit, and distressed debt. Founded in 2016 and headquartered in London, the privately held company reports adoption by 300+ financial institutions worldwide.