Founding Engineer
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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. Requirements 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, GitHub 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. #J-18808-Ljbffr
Vacancy posted 1 day ago
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