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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud & Backend Software Engineer - **Company:** ORBIT NEURO CO. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Amazon S3, Apache HTTP Server, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Storage, Databases, Computer Engineering, Continuous Delivery, Continuous Integration, Relational Databases, Database Design, PostgreSQL, MySQL, Message Queuing Telemetry Transport (MQTT), OAuth, Software Architecture, RabbitMQ, Openid Connect, Prometheus, SQL Databases, Data Streaming, Web Services, Parquet, Pulumi, Google Cloud, Data Storage Technologies, Grafana, Firebase, Indexer, Backend, Information Technology, Apache Kafka, Graphql, Terraform, Data Pipelines, Serverless Computing, Docker - **Published:** November 11, 2026 - **Apply:** https://startup.jobs/senior-cloud-backend-software-engineer-orbit-neuro-co-10727562 ## About the Role * An engineer with a degree in computer science, electrical engineering, computer engineering, or a related field, and at least five years of relevant professional experience. * Experienced designing and operating backend services, with depth in a modern production language. * Comfortable with data modeling, relational database design, SQL, APIs, and cloud object storage. * Familiar with authentication, authorization, and credential management across application boundaries. * Able to design robust data flows and reason about consistency between services, stored data, and metadata. * Interested in shaping a greenfield system, making tradeoffs explicit, and choosing designs a small team can build and evolve. * Someone who enjoys collaborating with the people producing and consuming the data. You might also * Have experience with Supabase or PostgreSQL row-level security (RLS), or bring related database and managed-backend experience with MySQL, Firebase, or Appwrite. * Have built REST or GraphQL APIs, serverless functions, event-driven services, or data ingestion pipelines on AWS, Google Cloud, or Azure. * Have worked with Zarr, HDF5, Apache Arrow, Parquet, or scientific datasets, and understand how storage formats support different access patterns. * Know object storage such as Amazon S3, Google Cloud Storage, or Azure Blob Storage, resumable uploads, or identity and access patterns using OAuth 2.0, OpenID Connect, or JWTs. * Have supported native desktop or connected-device clients, or built asynchronous data flows using MQTT, Apache Kafka, RabbitMQ, or comparable messaging technologies. * Have used infrastructure as code with Terraform or Pulumi, container tools such as Docker, or observability tools such as OpenTelemetry, Prometheus, and Grafana. * Bring experience with data provenance, reproducible processing, or datasets used in model development. We're looking for a strong foundation and the ability to grow. You don't need experience with every technology we use, and the "You might also" section is entirely optional. If the core work feels like a good match but some details are new to you, we'd like to hear from you. Prior neuroscience or brain-computer interface experience isn't expected. ## Description Build the data foundation that connects neural recordings to scientific discovery. This is a greenfield opportunity to shape our backend architecture, data model, database design, and the services that make recordings accessible and useful. You'll have real influence over technology choices and how the platform grows. Leading candidates include Supabase and PostgreSQL, with S3-compatible object storage and Zarr v3 for scientific arrays. We favor focused services and managed infrastructure that give a small team room to build ambitious capabilities. You will * Shape the backend architecture and select technologies around the needs of our product, researchers, and engineering team. * Design the data model and relational database schema, including recording identity, configuration, provenance, relationships, indexing, and schema migrations. * Build APIs and services for ingesting, storing, discovering, and retrieving recordings and their metadata. * Design authentication, authorization, and credential flows that make access secure and straightforward. * Collaborate with desktop engineers on robust upload and synchronization workflows that preserve recording integrity. * Develop scientific data storage around useful access patterns, balancing performance, scalability, and cost. * Establish automated testing, continuous integration and delivery (CI/CD), and observability that keep the platform reliable and easy to evolve.