LLM Data Engineer

Must-Have Requirements • Strong hands-on experience with AWS • Experience working with data sets, data sources, and AWS data services • Strong AI & LLM experience • Excellent communication skills • Active and complete LinkedIn profile • Healthcare experience is a plus, but not required Role Overview We are looking for a Generalist Data Engineer to support a healthcare-focused AI benchmark and evaluation platform. The engineer will be responsible for the data lifecycle before a model receives it and after the model generates a response. This includes building ingestion, normalization, packaging, storage, and analysis layers to transform raw healthcare data into standardized benchmark inputs and actionable evaluation results. Key Responsibilities • Build ingestion and normalization pipelines for: • DICOM radiology studies • Whole-slide pathology images • Tabular EHR data, including labs, vitals, encounters, and medication records • Design a canonical benchmark record format that can support different task configurations and model adapters • Develop strategies for packaging large medical imaging datasets within third-party API limitations • Build tiling, region selection, downsampling, and compression workflows while maintaining diagnostic information • Maintain provenance metadata to ensure results are reproducible and defensible • Develop cohort and label pipelines for clinical prediction tasks such as sepsis onset, survival horizons, and longitudinal lab trends • Build results storage and analysis layers for per-run, per-model, and per-task outputs • Enforce PHI handling requirements, including encryption, least-privilege access, audit logging, and de-identification • Ensure clear controls around data leaving the VPC when interacting with third-party APIs Required Skills: Data Engineering • Production-grade data pipeline development • Strong testing discipline • Experience building deterministic, idempotent, and re-runnable jobs AWS Data Stack • Deep hands-on experience with S3 • AWS Glue and/or Spark on EMR • Athena • Step Functions • Lambda • AWS Batch • Understanding of storage layout, lifecycle policies, and storage economics at scale SQL & Data Modeling • Complex temporal joins • Point-in-time correctness • Strong understanding of preventing label leakage in time-series data Data Quality & Lineage • Data validation frameworks • Schema enforcement • Versioned datasets • Data lineage and reproducibility AWS Security & Governance • IAM policy design • KMS • VPC endpoints and PrivateLink • Experience working within HIPAA-eligible AWS architectures Desirable Skills • Healthcare data standards including DICOM, FHIR, HL7v2, OMOP CDM • Familiarity with clinical coding systems such as ICD, LOINC, RxNorm, and SNOMED • Medical imaging experience with pydicom and OpenSlide • Understanding of WSI pyramid structures and tiling • Terraform / Infrastructure as Code • Docker, ECR, and CI/CD • Familiarity with LLM APIs and multimodal payload construction