Founding Engineer

Key Responsibilities

• Data pipelines: Build the pipelines that ingest, process, and transform data for the models.
• Cloud infrastructure: Stand up and operate compute, storage, networking, and deployment from scratch.
• Orchestration: Build the layer connecting ingestion, training, inference, evaluation, and serving.
• Operational foundations: Establish CI/CD, monitoring, logging, and alerting from the ground up.
• Application layer: Contribute to APIs, services, and user-facing surfaces on top of the platform.
• Technical strategy: Make foundational architectural decisions in direct partnership with the founders.

• Python and SQL fundamentals that are genuinely strong, not just familiar.
• Production data pipelines — hands-on experience with Airflow, Dagster, Prefect, or similar.
• Cloud proficiency — AWS, GCP, or Azure, including provisioning, IAM, and networking.
• Containers & orchestration — Docker and Kubernetes (or a managed equivalent).
• Infrastructure-as-code — Terraform, Pulumi, or CDK.
• Backend API design — REST, GraphQL, or gRPC, with working knowledge of auth.
• Relational database design — Postgres or similar, including query optimization.
• AI developer tooling — proficient with Claude Code, Cursor, Git Hub Copilot, or similar.
• Cross-stack debugging — a track record of operating across the stack and untangling complex systems.
• Engineering judgment — sound instincts on trade-offs, not just technical breadth.
• Nice to have: real-time streaming systems (Kafka, Pub/Sub, Kinesis, Flink); open-source contributions; experience with health or clinical data; full-stack product experience shipping user-facing web applications.