Full Job Description
WHAT YOU'LL DO
• Design and architect complex, scalable systems end-to-end. Making principled tradeoffs between performance, reliability, maintainability, and cost, and owning those decisions from whiteboard to production
• Design, build, and own scalable data pipelines for real-world health data from diverse sources
• Architect and implement production-grade AI-driven services for high-scale analysis of medical data.
• Build and operate robust backend services, APIs, and data products end-to-end. You design it, you build it, you run it
• Tackle genuinely hard distributed systems problems: low-latency access patterns, fault tolerance, consistency at scale
• Plan and build connection layers for EHR platforms and health APIs within isolated network environments
• Own cloud infrastructure end-to-end. Build systems that are repeatable, observable, and easy to change
• Drive engineering excellence: rigorous code and architecture reviews, testing strategies, and observability frameworks
• Partner with Data Science, Product, and Business to turn ambiguous requirements into production-grade solutions
WHO YOU ARE
• 5+ years building production software systems; care deeply about coding craft
• Fluent in Python, MCP and high scale / high throughout data pipelines
• Strong grasp of distributed systems, software architecture, and engineering fundamentals
• Experienced in building complex data pipelines and cloud-native systems on AWS
• Think holistically about correctness, performance, security, and cost
• Self-directed, clear communicator, thrive in a fast-moving startup with high ownership
• Genuinely excited by the mission: applying great engineering to improve patient outcomes
EXTRA CREDIT
• Experience in building a Large Language Model (LLM) pipeline (e.g., Qwen, Llama)
• Experience working with medical or clinical data (EHR, FHIR, HL7, claims, or de-identified patient datasets)
• Familiarity with data standardization frameworks, data cataloguing, or metadata management
• Experience with HIPAA compliance, data privacy, or healthcare security requirements
• Exposure to ML pipelines, feature stores, or working with data science teams
• A bachelor's, master's, or PhD in Computer Science or a related quantitative field
TECH STACK
Python • AWS • PostgreSQL • Elasticsearch • Terraform • Airflow / Prefect
