Hippocratic AI builds the safest generative AI healthcare agent for health systems, payors, and pharma. Over 180 million clinical interactions across 1,000+ use cases with 60+ partners worldwide. Backed by General Catalyst, Kleiner Perkins and a16z.
About the role
Hippocratic AI's AI agents are already working inside real hospitals and health systems — this role owns the backend infrastructure that keeps them fast, reliable, and ready to scale as that footprint grows. You'll architect systems built for tomorrow's volume, not just today's, working closely with data scientists, ML engineers, and product managers to turn healthcare requirements into production-grade infrastructure. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor's degree in Computer Science, Computer Engineering, or a related field (Master's preferred)
- 4+ years of backend development experience using Python, Golang, or similar languages
- Experience building and maintaining multi-modal (speech, vision, text) data pipelines using Ray, Apache Airflow, or similar for distributed processing and model experimentation, including distributed computing frameworks like Spark or Hadoop
- Familiarity with relational database systems and RESTful APIs
- Basic understanding of cloud infrastructure (AWS, GCP, or similar)
More about this role
Hippocratic AI's AI agents are already working inside real hospitals and health systems — this role owns the backend infrastructure that keeps them fast, reliable, and ready to scale as that footprint grows. You'll architect systems built for tomorrow's volume, not just today's, working closely with data scientists, ML engineers, and product managers to turn healthcare requirements into production-grade infrastructure.
Architect backend systems that sustain 99.9%+ uptime for high-volume healthcare data and LLM processing as usage grows exponentially
Implement monitoring that surfaces issues before they reach production AI agents
Own performance and reliability improvements across backend systems in collaboration with data scientists and ML engineers
Design data pipelines that ingest, process, and prepare large-scale, multi-modal (speech, vision, text) healthcare datasets for training and inference with minimal latency
Build tag management and metadata systems that make large datasets organized and retrievable
Develop and optimize infrastructure supporting data ingestion, feature extraction, and tagging workflows
Develop APIs and microservices that reduce processing time and...
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