Senior AI Data Engineer

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