Senior Cloud & Backend Software Engineer

The role

You will build the data foundation connecting neural recordings to scientific discovery. You will shape backend architecture, design data models, and build APIs and services.

What you will do

• Shape the backend architecture and select technologies.
• Design the data model and relational database schema.
• Build APIs and services for ingesting, storing, discovering, and retrieving recordings and metadata.
• Design authentication, authorization, and credential flows.
• Collaborate with desktop engineers on upload and synchronization workflows.
• Develop scientific data storage around useful access patterns.
• Establish automated testing, continuous integration and delivery (CI/CD), and observability.

Required qualifications

• Degree in computer science, electrical engineering, computer engineering, or a related field.
• 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.

Nice to have

• Experience with Supabase or PostgreSQL row-level security (RLS), or related database and managed-backend experience with MySQL, Firebase, or Appwrite.
• Built REST or GraphQL APIs, serverless functions, event-driven services, or data ingestion pipelines on AWS, Google Cloud, or Azure.
• Worked with Zarr, HDF5, Apache Arrow, Parquet, or scientific datasets.
• 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.
• Supported native desktop or connected-device clients, or built asynchronous data flows using MQTT, Apache Kafka, RabbitMQ, or comparable messaging technologies.
• Used infrastructure as code with Terraform or Pulumi, container tools such as Docker, or observability tools like OpenTelemetry, Prometheus, and Grafana.
• Experience with data provenance, reproducible processing, or datasets used in model development.

About the company

Orbit is a team of engineers, neuroscientists, and designers working to deepen understanding of the human brain. They are building a wearable brain-computer interface and models that decode emotion.