Full Stack Engineer

Software Engineer, AI & Data Platform (Python/Go)

Vancouver, BC · Remote (Canada)

Why this role is interesting

Most engineers building with LLMs right now are building chat interfaces. You'd be building something harder.

OneMedNet supplies regulatory-grade Real World Data and imaging Real World Data to life sciences, pharma, and medical device researchers. That means clinical records and medical imaging studies that have to be de-identified, curated, and validated to a standard that holds up under FDA scrutiny — at scale, across a growing network of hospital and clinic partners.

The interesting problems live in that gap: how do you use language models to accelerate curation of messy, high-stakes clinical data without ever compromising accuracy or patient privacy? How do you build inference pipelines that are auditable enough for a regulated environment? How do you make complex cohort data legible to a researcher in a browser?

That's the work.

What you'll do

• Build LLM-powered features for clinical data curation and retrieval — prompt design, evaluation, API integration, and the pipelines that hold it all together
• Design and ship backend services in Python and/or Go that move structured records, unstructured clinical notes, DICOM imaging, and HL7/FHIR messaging securely and fast
• Answer questions that close deals. When Sales is scoping a contract, someone has to query partner systems and determine what data actually exists and in what volume. That's engineering work, and it directly determines whether a deal happens
• Build the interfaces researchers actually use to search, filter, and visualize cohorts
• Own quality end to end: instrument your LLM features, monitor for drift and regression, and know when a model output is good enough to ship
• Work directly with the clinical and data teams who define what "regulatory grade" means for a given dataset

What we need from you

• 2+ years shipping production software with strong Python and/or Go
• Real experience building on LLM APIs (Anthropic, OpenAI, or similar) — you've shipped something that used one, and you've dealt with the failure modes
• Comfort across the stack. You don't need to be a design specialist, but you can build a functional, clear interface without waiting on someone else
• Strong SQL and database fundamentals — schema design, query performance, and knowing when relational is the wrong answer
• Working comfort in AWS and Linux. Our platform runs on AWS (S3, EC2, RDS, VPC, IAM) in Ubuntu environments. You should be able to operate there without hand-holding
• Judgment about correctness. In healthcare data, a plausible-but-wrong answer is worse than no answer. We need engineers who feel that in their bones

Our stack

Python and Go. AWS (S3, EC2, RDS, VPC, IAM) on Ubuntu Linux. Snowflake and Palantir for data and AI workloads. Anthropic and OpenAI APIs. Postgres. Git-based workflows.

Nice to have

• Healthcare, clinical data, or medical imaging experience (DICOM, HL7/FHIR)
• Working knowledge of HIPAA, GDPR, or technical de-identification techniques for PHI/PII
• Snowflake or Palantir experience
• Experience with model evaluation frameworks or LLM observability tooling
• Data visualization work

If you hit most of the core list and none of these, apply anyway. We'll teach you the healthcare part.

Compensation & benefits

• $80,000 – $120,000 CAD depending on experience, plus performance bonus
• Medical, dental, and vision insurance
• Unlimited PTO
• Flexible schedule and fully remote across Canada

• A small team at a real inflection point in an emerging market

• OneMedNet is committed to privacy and compliance, meeting or exceeding HIPAA, GDPR, and other applicable privacy standards to protect patient information.