Senior AI Data Engineer

Private Medical & Dental care & Life Insurance covered

Internal Mobility program - possibility of rotation between projects, locations, accounts

Join the Data Engineering team to contribute to the ongoing maintenance and improvement of an internal LLM-powered assistant that uses hosted LLM APIs and internal knowledge sources, with a focus on reliability, retrieval quality, and operational excellence.

• Maintain and enhance ingestion/enrichment pipelines for internal content (parsing/extraction, normalization, metadata enrichment, deduplication, and quality monitoring)
• Improve indexing and retrieval performance and quality (chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching) and support hybrid retrieval capabilities (vector + keyword/BM25 + metadata)
• Implement and maintain access‑aware retrieval by propagating/enforcing document permissions through indexing and query‑time filters, including audit logs and validation tests
• Improve source attribution so responses reliably point to the correct documents and sections in a consistent format
• Extend and harden tool/workflow execution and automations (scheduled/trigger‑based), including retries, timeouts, idempotency, concurrency controls, and run history
• Develop and maintain evaluation and regression testing (golden sets, automated scoring) and support structured comparisons across LLM providers/models as required
• Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

• 8+ years of hands‑on experience in Data Science and 5+ years in Machine Learning, with a proven track record, demonstrated through a robust portfolio of projects
• Strong programming skills in languages such as Python and familiarity building ETL pipelines
• Expertise in SQL and experience with both relational (preferably Postgres) and No
  
  SQL databases (Open Search or Elastic Search)
• Familiarity with cloud platforms (e.g., AWS) and their services
• Experience with version control systems (e.g., Git) and CI/CD pipelines
• Ability to build scalable infrastructure to embed and search very large number of documents
• Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
• Expertise in ML inference optimizations
• Solid experience with Hybrid RAG, chunking/segmentation refinements, embedding/index update workflows, metadata filtering, caching, etc.
• Knowledge of network optimization for distributed ML training and inference
• Understanding of distributed training patterns and checkpointing strategies
• Strong English skills (B2 and higher)
• Strong verbal and written communication skills
• Ability to work independently and collaborate in a group

• Agile certification
• AWS/Oracle/Microsoft attestations and certifications
• Domain knowledge - Trading and Capital Markets