Distributed Systems Engineer (Go/Python, Backend) – Remote

Doist; San Francisco (CA); Hybrid; USD 160,000 - 194,000; Full time

Benefits offered by this job

Equity grant

Medical, dental, vision

Flexible hours

Diversity & inclusion

Job summary

Verse is seeking a Software Engineer focused on distributed systems in San Francisco. Build cloud-native backend services that scale to trillions of data points from electricity markets worldwide, collaborating with engineers across product and platform teams.

You should enjoy shaping architecture, writing Go and Python, and driving deployment automation, observability, and security. This role offers hybrid work, competitive pay, and equity in a fast-growing energy AI company.

Qualifications

• Experience with distributed systems in a startup or scale-up setting.
• Strong command of Python or Go runtimes and build tools.
• Experience with monorepos and CI/CD workflows.
• Security awareness for scalable cloud services.

Responsibilities

• Foster well-designed, test-driven backend systems.
• Read and write Go, Python, and Protobuf code.
• Build and scale backend services and APIs.
• Migrate schemas and optimize queries for product work streams.
• Integrate with various storage systems across the stack.
• Troubleshoot and enhance system performance, reliability, and security.
• Collaborate with product managers, UX designers, and frontend engineers.
• Develop deployment automation and observability tools.

Skills

Python

Go

Distributed systems

Protobuf

gRPC

Container orchestration

Monorepo pipelines

Security fundamentals

Team leadership

Education

Bachelor's degree

Tools

Kubernetes

Google Cloud Platform

Protocol Buffers

GRPC

Go tooling

Job description

Verse is seeking a Software Engineer focused on distributed systems in San Francisco. Build cloud-native backend services that scale to trillions of data points from electricity markets worldwide, collaborating with engineers across product and platform teams.

You should enjoy shaping architecture, writing Go and Python, and driving deployment automation, observability, and security. This role offers hybrid work, competitive pay, and equity in a fast-growing energy AI company.