Note: The job is a remote job and is open to candidates in USA. Xaxis Solutions is seeking a Generalist Data Engineer to support a healthcare-focused AI benchmark and evaluation platform. The role will manage the data lifecycle before and after model processing by building ingestion, normalization, packaging, storage, and analysis layers for healthcare data, while ensuring data quality, reproducibility, security, and PHI compliance.
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
Skills
- 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
- Production-grade data pipeline development
- Strong testing discipline
- Experience building deterministic, idempotent, and re-runnable jobs
- 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
- Complex temporal joins
- Point-in-time correctness
- Strong understanding of preventing label leakage in time-series data
- Data validation frameworks
- Schema enforcement
- Versioned datasets
- Data lineage and reproducibility
- IAM policy design
- KMS
- VPC endpoints and PrivateLink
- Experience working within HIPAA-eligible AWS architectures
- Healthcare experience is a plus, but not required
- 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
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