AI Engineer
$170k - $220k USD
AI Engineer
Location: San Francisco (On-site)
Compensation: $170,000 – $220,000 + variable equity based on cash compensation
Technologies: Python, Pydantic AI, PostgreSQL, Linux, AWS, GCP, Langfuse, Modal, DuckDB, Fireworks, Baseten, Anthropic
About Us
Lotus Health is a groundbreaking primary care app that integrates your medical records, AI, and real doctors to provide free, personalized healthcare and prescriptions.
Our team includes ex-founders and engineers who have built and scaled consumer apps to millions of users, generating over $100M in annual revenue. Lotus is backed by Kleiner Perkins, and clinicians at Harvard and Stanford.
Role Overview
We’re looking for an AI Engineer to design and scale the data and retrieval systems that power Lotus’s clinical AI. You’ll work closely with the founding team to build the AI data layer — unifying fragmented health systems, improving correctness and traceability, and ensuring that our models surface fast, accurate, and explainable medical information. Your work will directly impact how medical knowledge is surfaced, validated, and applied in real-world care. This is a rare opportunity to join early, shape the core data foundation, and help define the future of accessible, intelligent healthcare.
Responsibilities
AI Knowledge Base and Search Improvements
Improve knowledge bases so that citations resolve to original data and searches are fast, relevant, and prioritize tier-one medical information.
Continuously enhance retrieval accuracy and data lineage tracking.
AI Data Ingestion and Integrity
Rebuild data pipelines to eliminate stale data, support clinician and patient corrections, and ensure full traceability.
Design models that sync cleanly with health data partners and credentialing authorities.
Observability and Analytics
Build monitoring and analytics for background jobs to monitor failure rates and identify partner vs. internal issues.
Streamline tracing, logging, and auditing to reduce redundancy while maintaining compliance-grade visibility.
Data Portability and Compliance
Enable seamless data migration between Lotus deployments with proper cache handling and deletion workflows.
Safeguard integrity and privacy during transfers.
What You Bring:
Strong proficiency in Python and SQL
Proven experience with system refactors, schema migrations, and data infrastructure simplification
Familiarity with PostgreSQL (including JSONB and vector types) and AWS
Experience building production systems that power AI or ML workflows
Comfort working across the stack, from schema design to production debugging
Curiosity, pragmatism, and a willingness to deeply understand complex data flows
Bonus Points:
Experience building retrieval systems for LLMs (RAG pipelines, vector search, grounding)
Familiarity with FastAPI, SQLAlchemy, DuckDB, Temporal, ClickHouse, Valkey, or similar systems
Knowledge of logging/monitoring stacks (Sentry, Langfuse) and containerized deployments (Docker, ECS)
Experience simplifying multi-layered data systems where architectural issues cascade through storage, logging, and application layers
Strong intuition for designing systems that balance correctness, observability, and performance
Why Lotus:
Join a team redefining how healthcare data is understood and acted upon. You’ll work with a world-class group of engineers, clinicians, and AI researchers to build something with lasting impact — accessible, free primary care for everyone.
As an AI Engineer on a small, exceptional team you’ll have the autonomy to build the systems that make our clinical AI safe, fast and explainable. On our small, exceptional team your work will directly influence patient care at scale.