Comp: $170k-270k base (DOE), generous equity and benefits

Fully remote based in US

NOT open to Visa holders at this point

We're looking for a Forward Deployed Engineer (3–8 years) to own end-to-end healthcare customer engagements at a fast-growing, VC-backed AI training data platform. You'll be the technical engine behind live deals — turning ambiguous, high-stakes healthcare data problems into delivered outcomes on tight timelines.

What you'll do

• Own customer engagements from scoping through delivery — translating vague requirements (e.g. 5M patient records spanning radiology, claims, genomics) into working data pipelines under pressure
• Build custom data engineering solutions to handle massive volumes of structured and unstructured healthcare data (imaging, EHR, claims) at scale
• Go on-site with customers and data partners to guide their engineering teams through working with data at scale
• Identify gaps between our platform and customer needs, and build the last-mile solutions that close them
• Surface repeatable patterns back to product to help turn bespoke implementations into scalable platform capabilities

What we're looking for

• Strong data engineering background building batch pipelines at massive scale, across structured and unstructured data (this is not a streaming-heavy environment)
• A track record of high ownership — founding engineer, early-stage startup, or equivalent end-to-end technical accountability
• Customer-facing experience: comfortable scoping ambiguous problems, communicating tradeoffs, and steering technical stakeholders away from preconceptions on the fly
• Strong SQL and hands-on ETL experience across diverse data formats
• A full-stack generalist mindset with a clear spike in data engineering
• Working understanding of AI/ML training workflows
• Comfort operating in PHI/HIPAA-compliant environments (healthcare domain expertise is a nice-to-have, not a requirement)
• Degree in Computer Science, Physics, or a related technical field
• Thrives in fast-paced, high-intensity environments — nights and weekends are common when deals are live

Tech stack: Python, SQL, batch data pipelines, structured & unstructured data, healthcare data (HL7/FHIR), PHI/HIPAA-compliant systems, cloud infrastructure (AWS/GCP/Azure), REST APIs, data integrations

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