How will you contribute? You'll be working on a production-grade Retrieval-Augmented Generation (RAG) system purpose-built for KYC and fund due diligence. The system must read and reason across heterogeneous document types, prospectuses, KIDs, AML/KYC reports, SFDR disclosures, extract structured signals, and support multi-agent workflows that assist analysts in forming risk-informed judgements. You will contribute to a system where document understanding quality and entity disambiguation accuracy translate directly into business impact. Code Development (60%):
- Build entity-centric retrieval pipelines that link references to the same fund, counterparty, or regulatory entity across multiple source documents
- Implement a document classification and completeness pipeline that identifies document type (prospectus, KID, AML report), scores KYC checklist coverage, and flags missing or inconsistent information
- Implement advanced chunking strategies optimised for long-form financial documents with complex tables, nested sections, and cross-references.
- Implement Visually rich document understanding (VRDU) techniques
- Build evaluation frameworks measuring entity extraction precision/recall, due diligence completeness, and end-to-end analyst decision support quality
- Optimise vector database indexing and retrieval for high-volume document ingestion across multiple fund data providers Research & experimentation (25%):
- Benchmark embedding models for financial domain specificity, focusing on regulatory terminology and entity semantics in fund documents.
- Explore cross-lingual capabilities for multilingual fund documents across EU jurisdictions (French, German, Luxembourgish regulatory variants)
- Research and prototype knowledge graph-based retrieval for cross-document entity relationships (fund → manager → counterparty → regulatory status)
- Experiment with multi-agent orchestration for parallel due diligence workflows, where specialised agents handle different document types or risk dimensions concurrently. System integration (15%):
- Integrate LLM backends optimised for structured extraction and integrate prompt engineering patterns tailored to KYC and due diligence reasoning tasks
- Implement comprehensive logging, monitoring, and audit trail generation to support compliance review of agent decisions in production Is Your profile described below? Are you our future colleague? Apply now! Education
- A PhD in Computer Science, Artificial Intelligence, or a closely related field is required.
- A background in Financial services domain is highly desirable. Experience and skills
- Preferably at least 2 years of research or industry experience in relevant areas. Must Have:
- Strong Python programming skills
- Hands on in LLMs RAG implementation.
- Experience with at least one ML framework (scikit-learn, transformers, etc.)
- Familiarity with data structures and algorithms
- Git proficiency for collaborative development Highly valued:
- Previous work with LangChain, LlamaIndex, or similar retrieval and agent orchestration frameworks
- Knowledge of multi agent workflow orchestration frameworks.
- Experience with NLP and entity extraction libraries (spaCy, NLTK, transformers) applied to financial or legal text
- Understanding of information retrieval concepts (BM25, TF-IDF, relevance scoring)
- Experience with React, Node.js or similar web frameworks
- Knowledge of evaluation methodologies for ML systems
- Track record of conducting application-driven AI research.
- Ability to work independently as well as collaboratively in interdisciplinary and multi-partner research environments.
- Familiarity with AML/KYC regulatory frameworks (FATF guidelines, EU AML Directives) or fund due diligence processes
- Experience with entity resolution or knowledge graph construction across heterogeneous document sources Language skills
- Fluency in English (and French), both oral and written. Other relevant languages are an asset. Your LIST benefits
- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Personalized learning programme to foster our staff's soft and technical skills
- Multicultural and international work environment with more than 60 nationalities represented in our workforce
- Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
- Gender-friendly environment with multiple actions to attract, develop and retain women in science
- 32 days' paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
- Flexible working hours, home working policy (not remote) and access to Digital lunch vouchers Apply online Your application must include:
- A motivation letter oriented towards the position and detailing your experience
- A scientific CV with contact details
- List of publications (and patents, if applicable)
- Contact details of 2 references Please apply ONLINE formally through the HR system. Applications by email will not be considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes. LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, ethnicity, gender, sexual orientation, gender identity, marital status, religion, age, or disability. Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above. As part of our recruitment process, the selected candidate might be subject to a background check in accordance with applicable laws and institutional policies. Further checks and restrictions might apply to candidates in compliance with export controls requirements
